Resources

Software Database

This database was constructed by Dr. Gary Skaggs as a repository of information on software created to perform or assist with psychometric analyses. It was created with support from the NCME Bradley Hanson Award. The database was last updated in July 2019.

Use the lists below to review software by type of analysis, license, and/or primary measurement model represented. Additional information about each software is provided further below.









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ANALYSIS

Attitude Scaling

Name Model License
BayesFM Latent Structure Open-Source (R)
covLCA Latent Structure Open-Source (R)
CTT Classical Open-Source (R)
GENOVA Classical Freeware
GGUM IRT/Rasch Open-Source (R)
IzstarMix IRT/Rasch Open-Source
Mixed-Up Suite Statistical Freeware
mixRasch IRT/Rasch Open-Source (R)
MSTGen IRT/Rasch Freeware
pcIRT IRT/Rasch Open-Source (R)
XCALIBRE IRT/Rasch Commercial

Cognitive Diagnostic Models

Name Model License
DIFboost Rasch Open-Source (R)
EQSIRT IRT/Rasch Commercial
EXTENSION Latent Structure Open-Source
mGENOVA Classical Freeware
PCMRS IRT/Rasch Open-Source (R)
PIE IRT/Rasch Freeware
TAM IRT/Rasch Open-Source (R)
WINSTEPS Rasch Commercial

Differential Item Functioning

Name Model License
BMIRT IRT/Rasch Freeware
Classical Form Assembly Classical Freeware
esaBcv Latent Structure Open-Source (R)
DIFlasso Rasch Open-Source (R)
DIF-Pack IRT/Rasch Open-Source
equate Classical Open-Source (R)
equateIRT IRT/Rasch Open-Source (R)
equateMultiple IRT/Rasch Open-Source (R)
esaBcv Latent Structure Open-Source (R)
GENOVA Classical Freeware
Integrity Utilities Commercial
IRT-Lab IRT/Rasch Freeware
ITEMAN Classical Commercial
IzstarMix IRT/Rasch Open-Source
kcirt IRT/Rasch Open-Source (R)
kequate Classical Open-Source (R)
Lertap5 Classical Commercial
lme4 Rasch Open-Source (R)
lslx Latent Structure Open-Source (R)
mGENOVA Classical Freeware
pairwise Rasch Open-Source (R)
PARSCALE IRT/Rasch Commercial
PP IRT/Rasch Open-Source (R)
PROC IRT IRT/Rasch Commercial
Psych Classical Open-Source (R)
psychmeta Statistical Open-Source (R)
psychometric Classical Open-Source (R)

Dimensionality

Name Model License
ACER ConQuest Rasch Commercial
CTTShiny Classical Open-Source (R)
DIFlasso Rasch Open-Source (R)
DIF-Pack IRT/Rasch Open-Source
emIRT IRT/Rasch Open-Source (R)
equateIRT IRT/Rasch Open-Source (R)
esaBcv Latent Structure Open-Source (R)
ETIRM IRT/Rasch Open-Source
EXTENSION Latent Structure Open-Source
faoutlier Latent Structure Open-Source (R)
G1 Classical Open-Source
IRT-Lab IRT/Rasch Freeware
lavaan Latent Structure Open-Source (R)
LEGS Classical Freeware
LinkMIRT IRT/Rasch Freeware
lordif IRT/Rasch Open-Source (R)
mdltm GDM IRT/Rasch Freeware
mirtCAT IRT/Rasch Open-Source (R)
mixRasch IRT/Rasch Open-Source (R)
MLwiN Statistical Commercial
MOKKEN IRT/Rasch Open-Source (R)
PCMRS IRT/Rasch Open-Source (R)
PIE IRT/Rasch Freeware
SEAsic Classical Open-Source (R)
sem Latent Structure Open-Source (R)
semPLS Latent Structure Open-Source (R)
semTools Latent Structure Open-Source (R)
ShortForm Classical Open-Source (R)
SIBTEST IRT/Rasch Open-Source (R)
SIMREL Classical Open-Source
simsem Latent Structure Open-Source (R)
SimulCAT IRT/Rasch Freeware
SimuMCAT IRT/Rasch Freeware
SimuMIRT IRT/Rasch Freeware
sirt IRT/Rasch Open-Source (R)
SNSequate IRT/Rasch Open-Source (R)
SparseFactorAnalysis Latent Structure Open-Source (R)
SPSS-AMOS Latent Structure Commercial
urGENOVA Classical Freeware
WinGen IRT/Rasch Freeware

Equating

Name Model License
Angoff Analysis Tool Classical Freeware
Arpeggio Suite IRT/Rasch Commercial
equate Classical Open-Source (R)
blavaan Latent Structure Open-Source (R)
cacIRT IRT/Rasch Open-Source (R)
CDM IRT/Rasch Open-Source (R)
CIPE Classical Freeware
CITAS Classical
equate Classical Open-Source (R)
Equating Error Classical Freeware
FastTEST PC Utilities Commercial
GGUM IRT/Rasch Open-Source (R)
immer Rasch Open-Source (R)
irr Classical Open-Source (R)
IRT Scoring IRT/Rasch Freeware
IRTEQ IRT/Rasch Freeware
IRT-Lab IRT/Rasch Freeware
jMetrik Classical Open-Source
kequate Classical Open-Source (R)
lme4 Rasch Open-Source (R)
MCMC GGUM IRT/Rasch Freeware
POLYEQUATE IRT/Rasch Freeware

Factor/Latent Structure

Name Model License
ctsem Latent Structure Open-Source (R)
CTTShiny Classical Open-Source (R)
DIFlasso Rasch Open-Source (R)
DIM-Pack Latent Structure Open-Source
emIRT IRT/Rasch Open-Source (R)
equateIRT IRT/Rasch Open-Source (R)
esaBcv Latent Structure Open-Source (R)
ETIRM IRT/Rasch Open-Source
EXTENSION Latent Structure Open-Source
faoutlier Latent Structure Open-Source (R)
GGUM2004 IRT/Rasch Freeware
IRTPRO IRT/Rasch Commercial
lavaan Latent Structure Open-Source (R)
LinkMIRT IRT/Rasch Freeware
lordif IRT/Rasch Open-Source (R)
MCMCglmm Rasch Open-Source (R)
mdltm GDM IRT/Rasch Freeware
mirtCAT IRT/Rasch Open-Source (R)
mixRasch IRT/Rasch Open-Source (R)
MLCIRTwithin IRT/Rasch Open-Source (R)
MLwiN Statistical Commercial
MOKKEN IRT/Rasch Open-Source (R)
nFactors Classical Open-Source (R)
RaschSampler Rasch Open-Source (R)
R-CODA Statistical Freeware
SEAsic Classical Open-Source (R)
sem Latent Structure Open-Source (R)
semPLS Latent Structure Open-Source (R)
semTools Latent Structure Open-Source (R)
ShortForm Classical Open-Source (R)
SIBTEST IRT/Rasch Open-Source (R)
SIMREL Classical Open-Source
simsem Latent Structure Open-Source (R)
SimulCAT IRT/Rasch Freeware
SimuMCAT IRT/Rasch Freeware
SimuMIRT IRT/Rasch Freeware
sirt IRT/Rasch Open-Source (R)
SNSequate IRT/Rasch Open-Source (R)
SparseFactorAnalysis Latent Structure Open-Source (R)
SPSS-AMOS Latent Structure Commercial
TAM IRT/Rasch Open-Source (R)
TestAssembler IRT/Rasch Commercial
TestScorer Classical Open-Source (R)
urGENOVA Classical Freeware
WINBUGS/BUGS IRT/Rasch Open-Source
WinGen IRT/Rasch Freeware

Generalizability

Name Model License
difR Classical Open-Source (R)
GDINA IRT/Rasch Open-Source (R)
IRTShiny IRT/Rasch Open-Source (R)
LISREL Latent Structure Commercial
mixRasch IRT/Rasch Open-Source (R)
WINMIRA Rasch Commercial

Interrater Reliability

Name Model License
elasticnet Latent Structure Open-Source (R)
mirtjml IRT/Rasch Open-Source (R)
mixRasch IRT/Rasch Open-Source (R)
MPlus Latent Structure Commercial

Item & Test Analysis

Name Model License
BayesFM Latent Structure Open-Source (R)
BayesLCA Latent Structure Open-Source (R)
ctsem Latent Structure Open-Source (R)
CATSim IRT/Rasch Commercial
CITAN Classical Freeware
Classical Form Assembly Classical Freeware
ConstructMap Rasch Freeware
Contrasting groups tool Classical Freeware
ctsem Latent Structure Open-Source (R)
CTTShiny Classical Open-Source (R)
DIFAS IRT/Rasch Freeware
DIFboost Rasch Open-Source (R)
DIFlasso Rasch Open-Source (R)
EQSIRT IRT/Rasch Commercial
equate Classical Open-Source (R)
esaBcv Latent Structure Open-Source (R)
EstCRM IRT/Rasch Open-Source (R)
EXTENSION Latent Structure Open-Source
Factor 9.2 IRT/Rasch Freeware
faoutlier Latent Structure Open-Source (R)
FitPMM IRT/Rasch Open-Source
flexMIRT IRT/Rasch Commercial
G1 Classical Open-Source
GENOVA Classical Freeware
GGUM2004 IRT/Rasch Freeware
GGUMLINK IRT/Rasch Freeware
GLAMM IRT/Rasch Freeware
GPCMlasso IRT/Rasch Open-Source (R)
gtheory Classical Open-Source (R)
HLM Statistical Commercial
HSGen IRT/Rasch Freeware
irtDemo IRT/Rasch Open-Source (R)
irtoys IRT/Rasch Open-Source (R)
IzstarMix IRT/Rasch Open-Source
jMetrik Classical Open-Source
kcirt IRT/Rasch Open-Source (R)
kequate Classical Open-Source (R)
lavaan Latent Structure Open-Source (R)
LEGS Classical Freeware
lme4 Rasch Open-Source (R)
lordif IRT/Rasch Open-Source (R)
ltm IRT/Rasch Open-Source
mcIRT IRT/Rasch Open-Source (R)
mGENOVA Classical Freeware
mirt IRT/Rasch Open-Source (R)
mirtCAT IRT/Rasch Open-Source (R)
mixRasch IRT/Rasch Open-Source (R)
MOKKEN IRT/Rasch Open-Source (R)
MPlus Latent Structure Commercial
mRm IRT/Rasch Open-Source (R)
nlsem Latent Structure Open-Source (R)
PARSCALE IRT/Rasch Commercial
pcIRT IRT/Rasch Open-Source (R)
PIE IRT/Rasch Freeware
PLmixed Latent Structure Open-Source (R)
plRasch Rasch Open-Source (R)
poLCA Latent Structure Open-Source (R)
polycor Utilities Open-Source (R)
POLYST IRT/Rasch Freeware
qcv Classical Open-Source (R)
RAGE-RGEQUATE Classical Freeware
randomLCA Latent Structure Open-Source (R)
ResidPlots-2 IRT/Rasch Freeware
rrum IRT/Rasch Open-Source (R)
rsem Latent Structure Open-Source (R)
RUMM Rasch Commercial
ScoreGGUM IRT/Rasch Open-Source (R)
ST IRT/Rasch Freeware
XCALIBRE IRT/Rasch Commercial

Latent Class Models

Name Model License
DIFAS IRT/Rasch Freeware
DIFtree IRT/Rasch Open-Source (R)
lordif IRT/Rasch Open-Source (R)
EQSIRT IRT/Rasch Commercial
EXTENSION Latent Structure Open-Source
GGUM2004 IRT/Rasch Freeware
IRT-Lab IRT/Rasch Freeware
IzstarMix IRT/Rasch Open-Source
lordif IRT/Rasch Open-Source (R)
MCMCglmm Rasch Open-Source (R)
mGENOVA Classical Freeware
nsprcomp Latent Structure Open-Source (R)
PCMRS IRT/Rasch Open-Source (R)
PIE IRT/Rasch Freeware
plRasch Rasch Open-Source (R)
poLCA Latent Structure Open-Source (R)
TAM IRT/Rasch Open-Source (R)
TestAssembler IRT/Rasch Commercial
TestScorer Classical Open-Source (R)
WinGen IRT/Rasch Freeware
WINSTEPS Rasch Commercial

Multidimensional Models

Name Model License
ACER ConQuest Rasch Commercial
BayesLCA Latent Structure Open-Source (R)
EXTENSION Latent Structure Open-Source
BigSEM Latent Structure Open-Source (R)
DIFboost Rasch Open-Source (R)
DIFlasso Rasch Open-Source (R)
DIM-Pack Latent Structure Open-Source
esaBcv Latent Structure Open-Source (R)
EXTENSION Latent Structure Open-Source
G1 Classical Open-Source
GGUM2004 IRT/Rasch Freeware
irtDemo IRT/Rasch Open-Source (R)
IRTEQ IRT/Rasch Freeware
IRT-Lab IRT/Rasch Freeware
IRTPRO IRT/Rasch Commercial
Latent Gold Latent Structure Commercial
LEGS Classical Freeware
LinkMIRT IRT/Rasch Freeware
lordif IRT/Rasch Open-Source (R)
MCMCglmm Rasch Open-Source (R)
mGENOVA Classical Freeware
mixRasch IRT/Rasch Open-Source (R)
MLCIRTwithin IRT/Rasch Open-Source (R)
MLwiN Statistical Commercial
MOKKEN IRT/Rasch Open-Source (R)
nFactors Classical Open-Source (R)
nsprcomp Latent Structure Open-Source (R)
PCMRS IRT/Rasch Open-Source (R)
PIE IRT/Rasch Freeware
R-CODA Statistical Freeware
ScoreGGUM IRT/Rasch Open-Source (R)
sem Latent Structure Open-Source (R)
semPLS Latent Structure Open-Source (R)
semTools Latent Structure Open-Source (R)
ShortForm Classical Open-Source (R)
SNSequate IRT/Rasch Open-Source (R)
TestAssembler IRT/Rasch Commercial
TestScorer Classical Open-Source (R)
urGENOVA Classical Freeware
WINBUGS/BUGS IRT/Rasch Open-Source
WinGen IRT/Rasch Freeware
WINSTEPS Rasch Commercial

Multilevel Data

Name Model License
CTTShiny Classical Open-Source (R)
DFIT IRT/Rasch Open-Source (R)
DIFAS IRT/Rasch Freeware
DIM-Pack Latent Structure Open-Source
dina IRT/Rasch Open-Source (R)
EXTENSION Latent Structure Open-Source
GGUM2004 IRT/Rasch Freeware
GLAMM IRT/Rasch Freeware
IRT-Lab IRT/Rasch Freeware
mGENOVA Classical Freeware
MPlus Latent Structure Commercial
RaschSampler Rasch Open-Source (R)
R-CODA Statistical Freeware
rsem Latent Structure Open-Source (R)
RUMM Rasch Commercial

Person Fit/Cheating

Name Model License
eRm Rasch Open-Source (R)
esaBcv Latent Structure Open-Source (R)
flexMIRT IRT/Rasch Commercial
gtheory Classical Open-Source (R)
IzstarMix IRT/Rasch Open-Source
kcirt IRT/Rasch Open-Source (R)
mGENOVA Classical Freeware
Mixed-Up Suite Statistical Freeware
MLCIRTwithin IRT/Rasch Open-Source (R)
pcIRT IRT/Rasch Open-Source (R)

Rater Effects

Name Model License
BayesLCA Latent Structure Open-Source (R)
Classical Form Assembly Classical Freeware
esaBcv Latent Structure Open-Source (R)
flexMIRT IRT/Rasch Commercial
kcirt IRT/Rasch Open-Source (R)
mirtjml IRT/Rasch Open-Source (R)
RUMM Rasch Commercial

Reliability

Name Model License
Contrasting groups tool Classical Freeware
equateIRT IRT/Rasch Open-Source (R)
lme4 Rasch Open-Source (R)
GGUMLINK IRT/Rasch Freeware
GLAMM IRT/Rasch Freeware
HSGen IRT/Rasch Freeware
IzstarMix IRT/Rasch Open-Source
jMetrik Classical Open-Source
lme4 Rasch Open-Source (R)
MCMCglmm Rasch Open-Source (R)
mirtCAT IRT/Rasch Open-Source (R)
mirtjml IRT/Rasch Open-Source (R)
mixRasch IRT/Rasch Open-Source (R)
MPlus Latent Structure Commercial
NOHARM IRT/Rasch Freeware
PARSCALE IRT/Rasch Commercial
rrum IRT/Rasch Open-Source (R)
ST IRT/Rasch Freeware
STDIF Classical Freeware

Scaling

Name Model License
BayesFM Latent Structure Open-Source (R)
BayesLCA Latent Structure Open-Source (R)
EstCRM IRT/Rasch Open-Source (R)
CATSim IRT/Rasch Commercial
Classical Form Assembly Classical Freeware
ctsem Latent Structure Open-Source (R)
equate Classical Open-Source (R)
equateIRT IRT/Rasch Open-Source (R)
EstCRM IRT/Rasch Open-Source (R)
Factor 9.2 IRT/Rasch Freeware
flexMIRT IRT/Rasch Commercial
GENOVA Classical Freeware
GGUM IRT/Rasch Open-Source (R)
GGUMLINK IRT/Rasch Freeware
Gifi Latent Structure Open-Source (R)
irtoys IRT/Rasch Open-Source (R)
kcirt IRT/Rasch Open-Source (R)
lme4 Rasch Open-Source (R)
MCMC GGUM IRT/Rasch Freeware
mGENOVA Classical Freeware
mixRasch IRT/Rasch Open-Source (R)
MultiLCIRT IRT/Rasch Open-Source (R)
PLmixed Latent Structure Open-Source (R)
STUIRT IRT/Rasch Freeware
xxIRT IRT/Rasch Open-Source (R)

Scoring

Name Model License
BayesFM Latent Structure Open-Source (R)
BayesLCA Latent Structure Open-Source (R)
equateIRT IRT/Rasch Open-Source (R)
CATSim IRT/Rasch Commercial
Classical Form Assembly Classical Freeware
ConstructMap Rasch Freeware
ctsem Latent Structure Open-Source (R)
equate Classical Open-Source (R)
equateIRT IRT/Rasch Open-Source (R)
esaBcv Latent Structure Open-Source (R)
EstCRM IRT/Rasch Open-Source (R)
Factor 9.2 IRT/Rasch Freeware
flirt IRT/Rasch Open-Source
GENOVA Classical Freeware
GGUMLINK IRT/Rasch Freeware
Gifi Latent Structure Open-Source (R)
GPCMlasso IRT/Rasch Open-Source (R)
HSGen IRT/Rasch Freeware
irtDemo IRT/Rasch Open-Source (R)
irtoys IRT/Rasch Open-Source (R)
irtProb IRT/Rasch Open-Source (R)
kcirt IRT/Rasch Open-Source (R)
kequate Classical Open-Source (R)
lme4 Rasch Open-Source (R)
mixRasch IRT/Rasch Open-Source (R)
MultiLCIRT IRT/Rasch Open-Source (R)
nlsem Latent Structure Open-Source (R)
pcIRT IRT/Rasch Open-Source (R)
polycor Utilities Open-Source (R)
POLYEQUATE IRT/Rasch Freeware
POLYST IRT/Rasch Freeware
STUIRT IRT/Rasch Freeware
xxIRT IRT/Rasch Open-Source (R)

Simulation/Resampling

Name Model License
BigSEM Latent Structure Open-Source (R)
BILOG-MG IRT/Rasch Commercial
CTTShiny Classical Open-Source (R)
DIM-Pack Latent Structure Open-Source
dina IRT/Rasch Open-Source (R)
emIRT IRT/Rasch Open-Source (R)
equateIRT IRT/Rasch Open-Source (R)
EXTENSION Latent Structure Open-Source
GGUM2004 IRT/Rasch Freeware
GPCMlasso IRT/Rasch Open-Source (R)
HLM Statistical Commercial
ICL 1.0 IRT/Rasch Freeware
IRT-Lab IRT/Rasch Freeware
IRTPRO IRT/Rasch Commercial
IzstarMix IRT/Rasch Open-Source
Latent Gold Latent Structure Commercial
MCMC Z-G IRT/Rasch Freeware
MCMCglmm Rasch Open-Source (R)
mirtCAT IRT/Rasch Open-Source (R)
Mixed-Up Suite Statistical Freeware
mixRasch IRT/Rasch Open-Source (R)
MLCIRTwithin IRT/Rasch Open-Source (R)
MLwiN Statistical Commercial
MOKKEN IRT/Rasch Open-Source (R)
nlsem Latent Structure Open-Source (R)
PCMRS IRT/Rasch Open-Source (R)
PLmixed Latent Structure Open-Source (R)
plRasch Rasch Open-Source (R)
poLCA Latent Structure Open-Source (R)
polycor Utilities Open-Source (R)
POLYST IRT/Rasch Freeware
PROC IRT IRT/Rasch Commercial
psychmeta Statistical Open-Source (R)
psychometric Classical Open-Source (R)
qcv Classical Open-Source (R)
RAGE-RGEQUATE Classical Freeware
SimuMCAT IRT/Rasch Freeware
sirt IRT/Rasch Open-Source (R)
TAM IRT/Rasch Open-Source (R)
WINBUGS/BUGS IRT/Rasch Open-Source
WINSTEPS Rasch Commercial
XCALIBRE IRT/Rasch Commercial

Test Construction & Administration

Name Model License
BILOG-MG IRT/Rasch Commercial
Facets Rasch Commercial
flirt IRT/Rasch Open-Source
ICL 1.0 IRT/Rasch Freeware
IzstarMix IRT/Rasch Open-Source
Latent Gold Latent Structure Commercial
MCMC Z-G IRT/Rasch Freeware
nlsem Latent Structure Open-Source (R)
NOHARM IRT/Rasch Freeware
polycor Utilities Open-Source (R)
psychomix IRT/Rasch Open-Source (R)
qcv Classical Open-Source (R)
xxIRT IRT/Rasch Open-Source (R)

Validity

Name Model License
DIM-Pack Latent Structure Open-Source
EXTENSION Latent Structure Open-Source
MCMCglmm Rasch Open-Source (R)
subscore Classical Open-Source (R)

SOFTWARE LICENSE

Commercial

Applications that must be purchased from a vendor.

Name Model Analyses
ACER ConQuest Rasch Dimensionality; Multidimensional Models
Arpeggio Suite IRT/Rasch Equating
flexMIRT IRT/Rasch Item & Test Analysis; Person Fit/Cheating; Rater Effects; Scaling
BILOG-MG IRT/Rasch Simulation/Resampling; Test Construction & Administration
CATSim IRT/Rasch Item & Test Analysis; Scaling; Scoring
EQSIRT IRT/Rasch Cognitive Diagnostic Models; Item & Test Analysis; Latent Class Models
Facets Rasch Test Construction & Administration
FastTEST PC Utilities Equating
flexMIRT IRT/Rasch Item & Test Analysis; Person Fit/Cheating; Rater Effects; Scaling
HLM Statistical Item & Test Analysis; Simulation/Resampling; General IRT concepts/graphics
Integrity Utilities DIF; Item & Test Analysis
IRTPRO IRT/Rasch Factor/Latent Structure; Multidimensional Models; Simulation/Resampling
ITEMAN Classical DIF; Differential test functioning and differential step function
Latent Gold Latent Structure Multidimensional Models; Simulation/Resampling; Test Construction & Administration
Lertap5 Classical DIF
LISREL Latent Structure Generalizability
MLwiN Statistical Dimensionality; Factor/Latent Structure; Multidimensional Models; Simulation/Resampling
MPlus Latent Structure Interrater Reliability; Interrater Reliability; Item & Test Analysis; Multilevel Data; Reliability; Meta-analysis; classical utility analysis; various correlati
PARSCALE IRT/Rasch DIF; Item & Test Analysis; Reliability; cheating detection
PROC IRT IRT/Rasch DIF; Simulation/Resampling
RUMM Rasch Item & Test Analysis; Multilevel Data; Rater Effects
SPSS-AMOS Latent Structure Dimensionality; Factor/Latent Structure; SEM
TestAssembler IRT/Rasch Factor/Latent Structure; Latent Class Models; Multidimensional Models
WINMIRA Rasch Generalizability
WINSTEPS Rasch Cognitive Diagnostic Models; Latent Class Models; Multidimensional Models; Simulation/Resampling
XCALIBRE IRT/Rasch Attitude Scaling; Item & Test Analysis; Simulation/Resampling

Freeware

Applications free to the user.

Name Model Analyses
Angoff Analysis Tool Classical Equating
BMIRT IRT/Rasch DIF
DIFAS IRT/Rasch Item & Test Analysis; Latent Class Models; Multilevel Data
CIPE Classical Equating
CITAN Classical Item & Test Analysis; graphs item characteristic curves
Classical Form Assembly Classical DIF; Item & Test Analysis; Rater Effects; Scaling; Scoring
ConstructMap Rasch Item & Test Analysis; Scoring
Contrasting groups tool Classical Item & Test Analysis; Reliability
DIFAS IRT/Rasch Item & Test Analysis; Latent Class Models; Multilevel Data
Equating Error Classical Equating
Factor 9.2 IRT/Rasch Item & Test Analysis; Scaling; Scoring; MCMC estimation
GENOVA Classical Attitude Scaling; DIF; Item & Test Analysis; Scaling; Scoring
GGUM2004 IRT/Rasch Factor/Latent Structure; Item & Test Analysis; Latent Class Models; Multidimensional Models; Multilevel Data; Simulation/Resampling
GGUMLINK IRT/Rasch Item & Test Analysis; Reliability; Scaling; Scoring
GLAMM IRT/Rasch Item & Test Analysis; Multilevel Data; Reliability
HSGen IRT/Rasch Item & Test Analysis; Reliability; Scoring
ICL 1.0 IRT/Rasch Simulation/Resampling; Test Construction & Administration
IRT Scoring IRT/Rasch Equating
IRTEQ IRT/Rasch Equating; Multidimensional Models
IRT-Lab IRT/Rasch DIF; Dimensionality; Equating; Latent Class Models; Multidimensional Models; Multilevel Data; Simulation/Resampling
LEGS Classical Dimensionality; Item & Test Analysis; Multidimensional Models
LinkMIRT IRT/Rasch Dimensionality; Factor/Latent Structure; Multidimensional Models
MCMC GGUM IRT/Rasch Equating; Scaling
MCMC Z-G IRT/Rasch Simulation/Resampling; Test Construction & Administration; CAT
mdltm GDM IRT/Rasch Dimensionality; Factor/Latent Structure
mGENOVA Classical Cognitive Diagnostic Models; DIF; Item & Test Analysis; Latent Class Models; Multidimensional Models; Multilevel Data; Person Fit/Cheating; Scaling
Mixed-Up Suite Statistical Attitude Scaling; Person Fit/Cheating; Simulation/Resampling
MSTGen IRT/Rasch Attitude Scaling
NOHARM IRT/Rasch Reliability; Test Construction & Administration
PIE IRT/Rasch Cognitive Diagnostic Models; Dimensionality; Item & Test Analysis; Latent Class Models; Multidimensional Models; MCMC
POLYEQUATE IRT/Rasch Equating; Scoring
RAGE-RGEQUATE Classical Item & Test Analysis; Simulation/Resampling
R-CODA Statistical Factor/Latent Structure; Multidimensional Models; Multilevel Data
ResidPlots-2 IRT/Rasch Item & Test Analysis
SimulCAT IRT/Rasch Dimensionality; Factor/Latent Structure; SEM
SimuMCAT IRT/Rasch Dimensionality; Factor/Latent Structure; Simulation/Resampling; SEM
SimuMIRT IRT/Rasch Dimensionality; Factor/Latent Structure; SEM
ST IRT/Rasch Item & Test Analysis; Reliability
STDIF Classical Reliability
STUIRT IRT/Rasch Scaling; Scoring
urGENOVA Classical Dimensionality; Factor/Latent Structure; Multidimensional Models; Bayesian latent variable models
WinGen IRT/Rasch Dimensionality; Factor/Latent Structure; Latent Class Models; Multidimensional Models

Open-source: R

Applications free to the user, with source code available. Available as packages or functions in R.

Name Model Analyses
BayesFM Latent Structure Attitude Scaling; Item & Test Analysis; Scaling; Scoring
BayesLCA Latent Structure Item & Test Analysis; Multidimensional Models; Rater Effects; Scaling; Scoring
covLCA Latent Structure Attitude Scaling
BigSEM Latent Structure Multidimensional Models; Simulation/Resampling
blavaan Latent Structure Equating
cacIRT IRT/Rasch Equating
CDM IRT/Rasch Equating
cocron Classical standard setting
covLCA Latent Structure Attitude Scaling
ctsem Latent Structure Factor/Latent Structure; Item & Test Analysis; Scaling; Scoring
CTT Classical Attitude Scaling
CTTShiny Classical Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multilevel Data; Simulation/Resampling
DFIT IRT/Rasch Multilevel Data
DIFboost Rasch Cognitive Diagnostic Models; Item & Test Analysis; Multidimensional Models
DIFlasso Rasch DIF; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models
difR Classical Generalizability
DIFtree IRT/Rasch Latent Class Models
dina IRT/Rasch Multilevel Data; Simulation/Resampling
elasticnet Latent Structure Interrater Reliability; Interrater Reliability
emIRT IRT/Rasch Dimensionality; Factor/Latent Structure; Simulation/Resampling
equate Classical DIF; Equating; Item & Test Analysis; Scaling; Scoring
equateIRT IRT/Rasch DIF; Dimensionality; Factor/Latent Structure; Reliability; Scaling; Scoring; Simulation/Resampling; MCMC
equateMultiple IRT/Rasch DIF
eRm Rasch Person Fit/Cheating
esaBcv Latent Structure DIF; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models; Person Fit/Cheating; Rater Effects; Scoring
EstCRM IRT/Rasch Item & Test Analysis; Scaling; Scoring
faoutlier Latent Structure Dimensionality; Factor/Latent Structure; Item & Test Analysis
GDINA IRT/Rasch Generalizability
GGUM IRT/Rasch Attitude Scaling; Equating; Scaling
Gifi Latent Structure Scaling; Scoring
GPCMlasso IRT/Rasch Item & Test Analysis; Scoring; Simulation/Resampling
immer Rasch Equating
irr Classical Equating
irtDemo IRT/Rasch Item & Test Analysis; Multidimensional Models; Scoring
irtoys IRT/Rasch Item & Test Analysis; Scaling; Scoring; nonparametric IRT
irtProb IRT/Rasch Scoring
IRTShiny IRT/Rasch Generalizability
kcirt IRT/Rasch DIF; Item & Test Analysis; Person Fit/Cheating; Rater Effects; Scaling; Scoring
kequate Classical DIF; Equating; Item & Test Analysis; Scoring
lavaan Latent Structure Dimensionality; Factor/Latent Structure; Item & Test Analysis
lme4 Rasch DIF; Equating; Item & Test Analysis; Reliability; Scaling; Scoring; Rasch models
lordif IRT/Rasch Dimensionality; Factor/Latent Structure; Item & Test Analysis; Latent Class Models; Multidimensional Models
lslx Latent Structure DIF
MAT IRT/Rasch diagnostics from MCMC output
mcIRT IRT/Rasch Item & Test Analysis
MCMCglmm Rasch Factor/Latent Structure; Latent Class Models; Multidimensional Models; Reliability; Simulation/Resampling; Validity
mirt IRT/Rasch Item & Test Analysis; IRT model fit
mirtCAT IRT/Rasch Dimensionality; Factor/Latent Structure; Item & Test Analysis; Reliability; Simulation/Resampling
mirtjml IRT/Rasch Interrater Reliability; Interrater Reliability; Rater Effects; Reliability; Sample size calculation for reliability
mixRasch IRT/Rasch Attitude Scaling; Dimensionality; Factor/Latent Structure; Generalizability; Interrater Reliability; Interrater Reliability; Item & Test Analysis; Multidimensional Models; Reliability; Scaling; Scoring; Simulation/Resampling
MLCIRTwithin IRT/Rasch Factor/Latent Structure; Multidimensional Models; Person Fit/Cheating; Simulation/Resampling
MOKKEN IRT/Rasch Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models; Simulation/Resampling
mRm IRT/Rasch Item & Test Analysis
MultiLCIRT IRT/Rasch Scaling; Scoring
nFactors Classical Factor/Latent Structure; Multidimensional Models
nlsem Latent Structure Item & Test Analysis; Scoring; Simulation/Resampling; Test Construction & Administration
nsprcomp Latent Structure Latent Class Models; Multidimensional Models
pairwise Rasch DIF; Mixture Models
pcIRT IRT/Rasch Attitude Scaling; Item & Test Analysis; Person Fit/Cheating; Scoring
PCMRS IRT/Rasch Cognitive Diagnostic Models; Dimensionality; Latent Class Models; Multidimensional Models; Simulation/Resampling; MCMC
PLmixed Latent Structure Item & Test Analysis; Scaling; Simulation/Resampling
plRasch Rasch Item & Test Analysis; Latent Class Models; Simulation/Resampling
poLCA Latent Structure Item & Test Analysis; Latent Class Models; Simulation/Resampling
polycor Utilities Item & Test Analysis; Scoring; Simulation/Resampling; Test Construction & Administration
PP IRT/Rasch DIF
Psych Classical DIF
psychmeta Statistical DIF; Simulation/Resampling
psychometric Classical DIF; Simulation/Resampling
psychomix IRT/Rasch Test Construction & Administration
qcv Classical Item & Test Analysis; Simulation/Resampling; Test Construction & Administration
randomLCA Latent Structure Item & Test Analysis
RaschSampler Rasch Factor/Latent Structure; Multilevel Data
cacIRT IRT/Rasch Equating
rrum IRT/Rasch Item & Test Analysis; Reliability
rsem Latent Structure Item & Test Analysis; Multilevel Data
ScoreGGUM IRT/Rasch Item & Test Analysis; Multidimensional Models; Scoring
SEAsic Classical Dimensionality; Factor/Latent Structure; Multidimensional Models
sem Latent Structure Dimensionality; Factor/Latent Structure; Multidimensional Models
semPLS Latent Structure Dimensionality; Factor/Latent Structure; Multidimensional Models
semTools Latent Structure Dimensionality; Factor/Latent Structure; Multidimensional Models
ShortForm Classical Dimensionality; Factor/Latent Structure; Multidimensional Models
SIBTEST IRT/Rasch Dimensionality; Factor/Latent Structure; SEM
simsem Latent Structure Dimensionality; Factor/Latent Structure; SEM
sirt IRT/Rasch Dimensionality; Factor/Latent Structure; Simulation/Resampling; SEM
SNSequate IRT/Rasch Dimensionality; Factor/Latent Structure; Multidimensional Models; SEM
SparseFactorAnalysis Latent Structure Dimensionality; Factor/Latent Structure; SEM
subscore Classical Validity
TAM IRT/Rasch Cognitive Diagnostic Models; Factor/Latent Structure; Latent Class Models; Simulation/Resampling
TestScorer Classical Factor/Latent Structure; Latent Class Models; Multidimensional Models
WrightMap IRT/Rasch meta-analysis
xxIRT IRT/Rasch Scaling; Scoring; Test Construction & Administration

Open-source: Other

Applications free to the user, with source code available.

Name Model Analyses
DIF-Pack IRT/Rasch DIF; Dimensionality
DIM-Pack Latent Structure Factor/Latent Structure; Multidimensional Models; Multilevel Data; Simulation/Resampling; Validity
IzstarMix IRT/Rasch Attitude Scaling; DIF; Item & Test Analysis; Latent Class Models; Person Fit/Cheating; Reliability; Simulation/Resampling; Test Construction & Administration
ETIRM IRT/Rasch Dimensionality; Factor/Latent Structure
EXTENSION Latent Structure Cognitive Diagnostic Models; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Latent Class Models; Multidimensional Models; Multilevel Data; Simulation/Resampling; Validity
FitPMM IRT/Rasch Item & Test Analysis
flirt IRT/Rasch Scoring; Test Construction & Administration
G1 Classical Dimensionality; Item & Test Analysis; Multidimensional Models
IzstarMix IRT/Rasch Attitude Scaling; DIF; Item & Test Analysis; Latent Class Models; Person Fit/Cheating; Reliability; Simulation/Resampling; Test Construction & Administration
jMetrik Classical Equating; Item & Test Analysis; Reliability
ltm IRT/Rasch Item & Test Analysis
SIMREL Classical Dimensionality; Factor/Latent Structure
WINBUGS/BUGS IRT/Rasch Factor/Latent Structure; Multidimensional Models; Simulation/Resampling; MCMC

MEASUREMENT MODEL

Classical Test Theory

Applications that are based primarily on true-score models.

Name License Analyses
Angoff Analysis Tool Freeware Equating
CIPE Freeware Equating
CTT Open-Source (R) Attitude Scaling
CITAN Freeware Item & Test Analysis; graphs item characteristic curves
CITAS Equating
Classical Form Assembly Freeware DIF; Item & Test Analysis; Rater Effects; Scaling; Scoring
cocron Open-Source (R) standard setting
Contrasting groups tool Freeware Item & Test Analysis; Reliability
CTT Open-Source (R) Attitude Scaling
CTTShiny Open-Source (R) Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multilevel Data; Simulation/Resampling
difR Open-Source (R) Generalizability
equate Open-Source (R) DIF; Equating; Item & Test Analysis; Scaling; Scoring
Equating Error Freeware Equating
G1 Open-Source Dimensionality; Item & Test Analysis; Multidimensional Models
GENOVA Freeware Attitude Scaling; DIF; Item & Test Analysis; Scaling; Scoring
gtheory Open-Source (R) Item & Test Analysis; Person Fit/Cheating
irr Open-Source (R) Equating
ITEMAN Commercial DIF; Differential test functioning and differential step function
jMetrik Open-Source Equating; Item & Test Analysis; Reliability
kequate Open-Source (R) DIF; Equating; Item & Test Analysis; Scoring
LEGS Freeware Dimensionality; Item & Test Analysis; Multidimensional Models
Lertap5 Commercial DIF
mGENOVA Freeware Cognitive Diagnostic Models; DIF; Item & Test Analysis; Latent Class Models; Multidimensional Models; Multilevel Data; Person Fit/Cheating; Scaling
nFactors Open-Source (R) Factor/Latent Structure; Multidimensional Models
Psych Open-Source (R) DIF
psychometric Open-Source (R) DIF; Simulation/Resampling
qcv Open-Source (R) Item & Test Analysis; Simulation/Resampling; Test Construction & Administration
RAGE-RGEQUATE Freeware Item & Test Analysis; Simulation/Resampling
SEAsic Open-Source (R) Dimensionality; Factor/Latent Structure; Multidimensional Models
ShortForm Open-Source (R) Dimensionality; Factor/Latent Structure; Multidimensional Models
SIMREL Open-Source Dimensionality; Factor/Latent Structure
subscore Open-Source (R) Validity
TestScorer Open-Source (R) Factor/Latent Structure; Latent Class Models; Multidimensional Models
urGENOVA Freeware Dimensionality; Factor/Latent Structure; Multidimensional Models; Bayesian latent variable models

Item Response Theory

Applications based on one or more latent trait models. Rasch models can be used by restricting parameters.

Name License Analyses
Arpeggio Suite Commercial Equating
BILOG-MG Commercial Simulation/Resampling; Test Construction & Administration
BMIRT Freeware DIF
cacIRT Open-Source (R) Equating
CATSim Commercial Item & Test Analysis; Scaling; Scoring
CDM Open-Source (R) Equating
DFIT Open-Source (R) Multilevel Data
DIFAS Freeware Item & Test Analysis; Latent Class Models; Multilevel Data
DIF-Pack Open-Source DIF; Dimensionality
DIFtree Open-Source (R) Latent Class Models
dina Open-Source (R) Multilevel Data; Simulation/Resampling
emIRT Open-Source (R) Dimensionality; Factor/Latent Structure; Simulation/Resampling
EQSIRT Commercial Cognitive Diagnostic Models; Item & Test Analysis; Latent Class Models
equateIRT Open-Source (R) DIF; Dimensionality; Factor/Latent Structure; Reliability; Scaling; Scoring; Simulation/Resampling; MCMC
equateMultiple Open-Source (R) DIF
EstCRM Open-Source (R) Item & Test Analysis; Scaling; Scoring
ETIRM Open-Source Dimensionality; Factor/Latent Structure
Factor 9.2 Freeware Item & Test Analysis; Scaling; Scoring; MCMC estimation
FitPMM Open-Source Item & Test Analysis
flexMIRT Commercial Item & Test Analysis; Person Fit/Cheating; Rater Effects; Scaling
flirt Open-Source Scoring; Test Construction & Administration
GDINA Open-Source (R) Generalizability
GGUM Open-Source (R) Attitude Scaling; Equating; Scaling
GGUM2004 Freeware Factor/Latent Structure; Item & Test Analysis; Latent Class Models; Multidimensional Models; Multilevel Data; Simulation/Resampling
GGUMLINK Freeware Item & Test Analysis; Reliability; Scaling; Scoring
GLAMM Freeware Item & Test Analysis; Multilevel Data; Reliability
GPCMlasso Open-Source (R) Item & Test Analysis; Scoring; Simulation/Resampling
HSGen Freeware Item & Test Analysis; Reliability; Scoring
ICL 1.0 Freeware Simulation/Resampling; Test Construction & Administration
IRT Scoring Freeware Equating
irtDemo Open-Source (R) Item & Test Analysis; Multidimensional Models; Scoring
IRTEQ Freeware Equating; Multidimensional Models
IRT-Lab Freeware DIF; Dimensionality; Equating; Latent Class Models; Multidimensional Models; Multilevel Data; Simulation/Resampling
irtoys Open-Source (R) Item & Test Analysis; Scaling; Scoring; nonparametric IRT
IRTPRO Commercial Factor/Latent Structure; Multidimensional Models; Simulation/Resampling
irtProb Open-Source (R) Scoring
IRTShiny Open-Source (R) Generalizability
IzstarMix Open-Source Attitude Scaling; DIF; Item & Test Analysis; Latent Class Models; Person Fit/Cheating; Reliability; Simulation/Resampling; Test Construction & Administration
kcirt Open-Source (R) DIF; Item & Test Analysis; Person Fit/Cheating; Rater Effects; Scaling; Scoring
LinkMIRT Freeware Dimensionality; Factor/Latent Structure; Multidimensional Models
lordif Open-Source (R) Dimensionality; Factor/Latent Structure; Item & Test Analysis; Latent Class Models; Multidimensional Models
ltm Open-Source Item & Test Analysis
MAT Open-Source (R) diagnostics from MCMC output
mcIRT Open-Source (R) Item & Test Analysis
MCMC GGUM Freeware Equating; Scaling
MCMC Z-G Freeware Simulation/Resampling; Test Construction & Administration; CAT
mdltm GDM Freeware Dimensionality; Factor/Latent Structure
mirt Open-Source (R) Item & Test Analysis; IRT model fit
mirtCAT Open-Source (R) Dimensionality; Factor/Latent Structure; Item & Test Analysis; Reliability; Simulation/Resampling
mirtjml Open-Source (R) Interrater Reliability; Interrater Reliability; Rater Effects; Reliability; Sample size calculation for reliability
mixRasch Open-Source (R) Attitude Scaling; Dimensionality; Factor/Latent Structure; Generalizability; Interrater Reliability; Interrater Reliability; Item & Test Analysis; Multidimensional Models; Reliability; Scaling; Scoring; Simulation/Resampling
MLCIRTwithin Open-Source (R) Factor/Latent Structure; Multidimensional Models; Person Fit/Cheating; Simulation/Resampling
MOKKEN Open-Source (R) Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models; Simulation/Resampling
mRm Open-Source (R) Item & Test Analysis
MSTGen Freeware Attitude Scaling
MultiLCIRT Open-Source (R) Scaling; Scoring
NOHARM Freeware Reliability; Test Construction & Administration
PARSCALE Commercial DIF; Item & Test Analysis; Reliability; cheating detection
pcIRT Open-Source (R) Attitude Scaling; Item & Test Analysis; Person Fit/Cheating; Scoring
PCMRS Open-Source (R) Cognitive Diagnostic Models; Dimensionality; Latent Class Models; Multidimensional Models; Simulation/Resampling; MCMC
PIE Freeware Cognitive Diagnostic Models; Dimensionality; Item & Test Analysis; Latent Class Models; Multidimensional Models; MCMC
POLYEQUATE Freeware Equating; Scoring
POLYST Freeware Item & Test Analysis; Scoring; Simulation/Resampling
PP Open-Source (R) DIF
PROC IRT Commercial DIF; Simulation/Resampling
psychomix Open-Source (R) Test Construction & Administration
ResidPlots-2 Freeware Item & Test Analysis
rrum Open-Source (R) Item & Test Analysis; Reliability
ScoreGGUM Open-Source (R) Item & Test Analysis; Multidimensional Models; Scoring
SIBTEST Open-Source (R) Dimensionality; Factor/Latent Structure; SEM
SimulCAT Freeware Dimensionality; Factor/Latent Structure; SEM
SimuMCAT Freeware Dimensionality; Factor/Latent Structure; Simulation/Resampling; SEM
SimuMIRT Freeware Dimensionality; Factor/Latent Structure; SEM
sirt Open-Source (R) Dimensionality; Factor/Latent Structure; Simulation/Resampling; SEM
SNSequate Open-Source (R) Dimensionality; Factor/Latent Structure; Multidimensional Models; SEM
ST Freeware Item & Test Analysis; Reliability
STUIRT Freeware Scaling; Scoring
TAM Open-Source (R) Cognitive Diagnostic Models; Factor/Latent Structure; Latent Class Models; Simulation/Resampling
TestAssembler Commercial Factor/Latent Structure; Latent Class Models; Multidimensional Models
WINBUGS/BUGS Open-Source Factor/Latent Structure; Multidimensional Models; Simulation/Resampling; MCMC
WinGen Freeware Dimensionality; Factor/Latent Structure; Latent Class Models; Multidimensional Models
WrightMap Open-Source (R) meta-analysis
XCALIBRE Commercial Attitude Scaling; Item & Test Analysis; Simulation/Resampling
xxIRT Open-Source (R) Scaling; Scoring; Test Construction & Administration

Latent Structure

Applications where the primary purpose is to analyze the underlying structure of variables.

Name License Analyses
BayesFM Open-Source (R) Attitude Scaling; Item & Test Analysis; Scaling; Scoring
BayesLCA Open-Source (R) Item & Test Analysis; Multidimensional Models; Rater Effects; Scaling; Scoring
BigSEM Open-Source (R) Multidimensional Models; Simulation/Resampling
blavaan Open-Source (R) Equating
covLCA Open-Source (R) Attitude Scaling
ctsem Open-Source (R) Factor/Latent Structure; Item & Test Analysis; Scaling; Scoring
DIM-Pack Open-Source Factor/Latent Structure; Multidimensional Models; Multilevel Data; Simulation/Resampling; Validity
elasticnet Open-Source (R) Interrater Reliability; Interrater Reliability
esaBcv Open-Source (R) DIF; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models; Person Fit/Cheating; Rater Effects; Scoring
EXTENSION Open-Source Cognitive Diagnostic Models; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Latent Class Models; Multidimensional Models; Multilevel Data; Simulation/Resampling; Validity
faoutlier Open-Source (R) Dimensionality; Factor/Latent Structure; Item & Test Analysis
Gifi Open-Source (R) Scaling; Scoring
Latent Gold Commercial Multidimensional Models; Simulation/Resampling; Test Construction & Administration
lavaan Open-Source (R) Dimensionality; Factor/Latent Structure; Item & Test Analysis
LISREL Commercial Generalizability
lslx Open-Source (R) DIF
MPlus Commercial Interrater Reliability; Interrater Reliability; Item & Test Analysis; Multilevel Data; Reliability; Meta-analysis; classical utility analysis; various correlati
nlsem Open-Source (R) Item & Test Analysis; Scoring; Simulation/Resampling; Test Construction & Administration
nsprcomp Open-Source (R) Latent Class Models; Multidimensional Models
PLmixed Open-Source (R) Item & Test Analysis; Scaling; Simulation/Resampling
poLCA Open-Source (R) Item & Test Analysis; Latent Class Models; Simulation/Resampling
randomLCA Open-Source (R) Item & Test Analysis
rsem Open-Source (R) Item & Test Analysis; Multilevel Data
sem Open-Source (R) Dimensionality; Factor/Latent Structure; Multidimensional Models
semPLS Open-Source (R) Dimensionality; Factor/Latent Structure; Multidimensional Models
semTools Open-Source (R) Dimensionality; Factor/Latent Structure; Multidimensional Models
simsem Open-Source (R) Dimensionality; Factor/Latent Structure; SEM
SparseFactorAnalysis Open-Source (R) Dimensionality; Factor/Latent Structure; SEM
SPSS-AMOS Commercial Dimensionality; Factor/Latent Structure; SEM

Rasch

Applications based on latent trait models designed to achieve specific objectivity.

Name License Analyses
ACER ConQuest Commercial Dimensionality; Multidimensional Models
ConstructMap Freeware Item & Test Analysis; Scoring
lme4 Open-Source (R) DIF; Equating; Item & Test Analysis; Reliability; Scaling; Scoring; Rasch models
DIFboost Open-Source (R) Cognitive Diagnostic Models; Item & Test Analysis; Multidimensional Models
DIFlasso Open-Source (R) DIF; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models
eRm Open-Source (R) Person Fit/Cheating
Facets Commercial Test Construction & Administration
immer Open-Source (R) Equating
lme4 Open-Source (R) DIF; Equating; Item & Test Analysis; Reliability; Scaling; Scoring; Rasch models
MCMCglmm Open-Source (R) Factor/Latent Structure; Latent Class Models; Multidimensional Models; Reliability; Simulation/Resampling; Validity
pairwise Open-Source (R) DIF; Mixture Models
plRasch Open-Source (R) Item & Test Analysis; Latent Class Models; Simulation/Resampling
RaschSampler Open-Source (R) Factor/Latent Structure; Multilevel Data
RUMM Commercial Item & Test Analysis; Multilevel Data; Rater Effects
WINMIRA Commercial Generalizability
WINSTEPS Commercial Cognitive Diagnostic Models; Latent Class Models; Multidimensional Models; Simulation/Resampling

Statistical

Applications that provide quantitative analysis but are not based on a specific paradigm.

Name License Analyses
HLM Commercial Item & Test Analysis; Simulation/Resampling; General IRT concepts/graphics
Mixed-Up Suite Freeware Attitude Scaling; Person Fit/Cheating; Simulation/Resampling
MLwiN Commercial Dimensionality; Factor/Latent Structure; Multidimensional Models; Simulation/Resampling
psychmeta Open-Source (R) DIF; Simulation/Resampling
R-CODA Freeware Factor/Latent Structure; Multidimensional Models; Multilevel Data

Utilities

Applications that provide functions to support psychometric analyses.

Name License Analyses
FastTEST PC Commercial Equating
Integrity Commercial DIF; Item & Test Analysis
polycor Open-Source (R) Item & Test Analysis; Scoring; Simulation/Resampling; Test Construction & Administration

LIST OF ALL SOFTWARE

ACER ConQuest

Author: Raymond J. Adams, Margaret L. Wu, Mark R. Wilson.
Contact: http://acer-conquest.software.informer.com/
Description: ACER ConQuest 4 is a computer program for fitting both unidimensional and multidimensional item response and latent regression models. It provides data analysis based on a comprehensive and flexible range of item response models (IRM), allowing examination of the properties of performance assessments, traditional assessments and rating scales. ACER ConQuest 4 also offers wider measurement and research community analysis procedures based on the most up-to-date psychometric methods of multifaceted item response models, multidimensional item response models, latent regression models and drawing plausible values.
Analyses: Dimensionality; Multidimensional Models
System Requirements: Windows, Macs running Windows 32- & 64-bit versions
Measurement Model: Rasch
License Type: Commercial
Documentation: demo version & tutorials trial version available

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Angoff Analysis Tool

Author: Assessment Systems Corp.
Contact: http://www.assess.com/angoff-analysis-tool/
Description: The AAT supports best practices in implementing the modified-Angoff approach Utilize two rounds of ratings (Delphi method) to improve inter-rater reliability and validity Perform a reality check with the Beuk Compromise Estimate mean and SD of the exam forms using classical item statistics (P and Rpbis) Estimate a cutscore with the Hofstee, a completely separate method, as a parallel approach Evaluate pass rates with competing methods to consider candidate impact
Analyses: Equating
System Requirements:
Measurement Model: Classical
License Type: Freeware
Documentation:

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Arpeggio Suite

Author: Bolt, Chen, DiBello, Hartz, Henson, Roussos, Stout, Templin
Contact: Lou DiBello (ldibello@uic.edu)
Description: Diagnostic appraisals of examinee ability on multiple skills or multiple facets of understanding are often required in educational assessment, especially in formative assessment settings, and represent one of the most important lines of research in measurement today. The Arpeggio Suite is a statistical analysis package that runs in Windows, and is the first assessment package specifically designed for this cutting-edge type of analysis. Using the Fusion Model, a sophisticated and flexible IRT model developed for such analyses, Arpeggio classifies examinees as masters or nonmasters of the user-specified skills and provides information regarding the discrimination of items and the test as a whole with respect to those skills. Arpeggio is ideal for educational measurement research concerning skills diagnostics as well as for applied educational assessments where skills diagnostics are required to provide greater examinee feedback.
Analyses: Equating
System Requirements: Windows 95 or Higher
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation: manual; input/output files for sample analyses

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BayesFM

Author: Rémi Piatek
Contact: https://cran.r-project.org/web/packages/BayesFM/index.html
Description: BayesFM: Bayesian Inference for Factor Modeling. Collection of procedures to perform Bayesian analysis on a variety of factor models. Currently, it includes: Bayesian Exploratory Factor Analysis (befa), an approach to dedicated factor analysis with stochastic search on the structure of the factor loading matrix. The number of latent factors, as well as the allocation of the manifest variables to the factors, are not fixed a priori but determined during MCMC sampling. More approaches will be included in future releases of this package.
Analyses: Attitude Scaling; Item & Test Analysis; Scaling; Scoring
System Requirements: Windows, Linux, or Mac
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual

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BayesLCA

Author: Arthur White, Thomas Brendan Murphy
Contact: https://cran.r-project.org/web/packages/BayesLCA/index.html
Description: BayesLCA: Bayesian Latent Class Analysis. Bayesian Latent Class Analysis using several different methods.
Analyses: Item & Test Analysis; Multidimensional Models; Rater Effects; Scaling; Scoring
System Requirements: Windows, Linux, or Mac
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, sample dataset

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BigSEM

Author: Chen Chen, Dabao Zhang
Contact: https://cran.r-project.org/web/packages/BigSEM/index.html
Description: BigSEM: Constructing Large Systems of Structural Equations. Construct large systems of structural equations using the two-stage penalized least squares (2SPLS) method proposed by Chen, Zhang and Zhang (2016).
Analyses: Multidimensional Models; Simulation/Resampling
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, real and simulated datasets

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BILOG-MG

Author: Michele Zimowski, Eiji Muraki, Robert Mislevy & Da
Contact: www.ssicentral.com
Description: BILOG is designed for a wide range of applications of IRT to practical testing problems. It assumes binary (right-wrong) scoring of item responses and employs marginal maximum likelihood and Bayes estimation methods.
Analyses: Simulation/Resampling; Test Construction & Administration
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation: User's manual in PDF, online help

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blavaan

Author: Edgar Merkle, Yves Rosseel, Mauricio Garnier-Villarreal, Terrence D. J
Contact: https://cran.r-project.org/web/packages/blavaan/index.html
Description: blavaan: Bayesian Latent Variable Analysis. Fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models.
Analyses: Equating
System Requirements: Windows, Linux, or Mac
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual

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BMIRT

Author: Lihua Yao
Contact: http://www.bmirt.com/6271.html
Description: BMIRTII(Yao, 2003, 2010), Bayesian Multivariate item Response Theory, is a computer program that uses Markov chain Monte Carlo (MCMC) Metropolics-Hastings method to produce item and ability parameter estimates and model fit statistics such as AIC, BIC, DIC, in multidimensional, multi-group item response theory model frame work; exploratory and confirmatory mode are supported; it supports three-parameter logistic model, generalized two-parameter partial-credit model, graded response model, higher-order model, testlet model, and rater model.
Analyses: DIF
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation:

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cacIRT

Author: Quinn Lathrop
Contact: https://cran.r-project.org/web/packages/cacIRT
Description: The R package cacIRT computes classification accuracy (CA) and consistency (CC) following the approach proposed by Lee (2010) or the approach proposed by Rudner (2005). While implementations of both approaches are available from the respective authors as stand-alone programs, cacIRT provides both in a unified framework within R. In addition, procedures based on Rudner's approach are extended beyond the sample-based CA index by including a CC index and an option for distributional marginalization (called the D method, see Lee, 2010).
Analyses: Equating
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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CATSim

Author: Assessment Systems Corp.
Contact: http://www.assess.com/catsim/
Description: CATSim implements three types of simulations for computerized adaptive testing (CAT): post-hoc (real-data) simulations, hybrid simulations, and monte-carlo simulations. In implementing a CAT program, all three types of simulation can be used at various stages of the CAT development process. CATSim options allow you to implement all three types of simulations, varying CAT starting thetas, theta estimation methods, item selection methods, item exposure controls, and termination criteria. CATSim will implement simulations for item banks of up to 999 items, with no limit on the number of examinees for both post-hoc and hybrid simulations, and a limit of 10,000 examinees for monte-carlo simulations. However, CAT simulations can be done with as few as 200 examinees or fewer if they adequately represent the population to which the CAT will be applied. CATSim implements simulations for all three dichotomous item response theory (IRT) models and five polytomous IRT models. CATSim includes all of the CAT options in FastTest, our secure platform for online testing, so that the results of using CATSim can easily be implemented in your testing program.
Analyses: Item & Test Analysis; Scaling; Scoring
System Requirements:
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation:

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CDM

Author: Alexander Robitzsch, Thomas Kiefer, & Ann C. George
Contact: https://cran.r-project.org/web/packages/CDM
Description: Functions for cognitive diagnosis modeling and multidimensional item response modeling for dichotomous and polytomous item responses. This package enables the estimation of the DINA and DINO model (Junker & Sijtsma, 2001, <doi:10.1177/01466210122032064>), the multiple group (polytomous) GDINA model (de la Torre, 2011, <doi:10.1007/s11336-011-9207-7>), the multiple choice DINA model (de la Torre, 2009, <doi:10.1177/0146621608320523>), the general diagnostic model (GDM; von Davier, 2008, <doi:10.1348/000711007X193957>), the structured latent class model (SLCA; Formann, 1992, <doi:10.1080/01621459.1992.10475229>) and regularized latent class analysis (Chen, Li, Liu, & Ying, 2017, <doi:10.1007/s11336-016-9545-6>). See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) <doi:10.18637/jss.v074.i02> or Robitzsch and George (2019, <doi:10.1007/978-3-030-05584-4_26>) for further details on estimation and the package structure. For tutorials on how to use the CDM package see George and Robitzsch (2015, <doi:10.20982/tqmp.11.3.p189>) as well as Ravand and Robitzsch (2015).
Analyses: Equating
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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CIPE

Author: M. J. Kolen & Y. Chien
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: CIPE conducts linear and equipercentile equating under the common-item nonequivalent groups design.
Analyses: Equating
System Requirements: PC Console, PC GUI , MAC OS 9 , MAC OS10
Measurement Model: Classical
License Type: Freeware
Documentation: Manual in PDF format

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CITAN

Author: Richard M. Luecht
Contact: http://soe.uncg.edu/academics/departments/erm/erm-software/
Description: CITAN performs a classical test theory item analysis of selected-response items scored using dichotomous scoring rules. The program performs distractor analyses, including summarizing high-low group performance and providing distractor-test score correlations. CITAN also supports responses of varied widths and allows multiple answer keys for each item.
Analyses: Item & Test Analysis; graphs item characteristic curves
System Requirements: Windows
Measurement Model: Classical
License Type: Freeware
Documentation: Users Guide; sample code and data

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CITAS

Author: Assessment Systems Corp.
Contact: http://www.assess.com/citas/
Description: CITAS is an easy-to-use tool for implementing classical test theory on small data sets, designed to provide a straightforward and no-cost way for non-psychometricians to evaluate the quality of assessments. Note that these are all based on classical test theory, and therefore rely on raw number-correct scores. CITAS is limited to 50 examinees and 50 dichotomous items.
Analyses: Equating
System Requirements:
Measurement Model: Classical
License Type:
Documentation:

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Classical Form Assembly

Author: Assessment Systems Corp.
Contact: http://www.assess.com/classical-form-assembly-tool/
Description: The Classical Form Assembly Tool allows you to build up to three forms with parallel: Content distribution Projected score mean Projected score SD Projected reliability Cutscore (mean Angoff)
Analyses: DIF; Item & Test Analysis; Rater Effects; Scaling; Scoring
System Requirements:
Measurement Model: Classical
License Type: Freeware
Documentation:

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cocron

Author: Birk Diedenhofen
Contact: https://cran.r-project.org/web/packages/cocron/index.html
Description: cocron: Statistical Comparisons of Two or more Alpha Coefficients. Statistical tests for the comparison between two or more alpha coefficients based on either dependent or independent groups of individuals. A web interface is available at http://comparingcronbachalphas.org. A plugin for the R GUI and IDE RKWard is included. Please install RKWard from https:// rkward.kde.org to use this feature. The respective R package 'rkward' cannot be installed directly from a repository, as it is a part of RKWard.
Analyses: standard setting
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: user manual, sample dataset

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ConstructMap

Author: Kennedy, C.A., Wilson, M.R., Draney, K., Tutnciyan, S., & Vorp, R.
Contact: bearcenter.berkeley.edu/software/construct
Description: ConstructMap is a graphical, menu-driven software package that combines a multidimensional IRT engine for estimating item and person parameters with tools for managing cross-sectional and longitudinal student response data and interpreting findings from such data. Graphical maps and reports are designed for use in settings in which progress on multiple measures can be examined and analyzed. Users can select expected a posteriori (EAP), maximum likelihood, or plausible value estimates of multivariate proficiency estimates. ConstructMap accepts dichotomous, rating scale, or partial credit items in between-item (each response is an indicator of a single dimension) or within-item (a response may be an indicator of multiple dimensions) multidimensional models.
Analyses: Item & Test Analysis; Scoring
System Requirements: Windows, Mac, requires Java
Measurement Model: Rasch
License Type: Freeware
Documentation: online and PDF user guide, demonstrations of featu

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Contrasting groups tool

Author: Assessment Systems Corp.
Contact: http://www.assess.com/contrasting-groups-tool/
Description: A cutscore that is not empircally evidenced is not legally defensible. There are several accepted methods for setting a valid cutscore, and one of these is the contrasting groups method. It has the advantage over others in that it can be used in a purely data-driven way, in addition to being used with subject matter expert (SME) ratings. The goal of the contrasting groups method is to evaluate how test scores predict some sort of gold standard in classifying examinees. One example is a practice test. Suppose you are delivering a practice test for a national certification exam. You have 100 people take your test, and you also gather their Pass/Fail results from the national exam. Naturally, people who score higher on your exam are more likely to pass. We want to find the cutscore on your exam that best predicts this. The Contrasting Groups Tool allows you to paste in the test scores and the “gold standard and then recommends a cutscore from both a mimimized-error and smoothed-distribution perspective.
Analyses: Item & Test Analysis; Reliability
System Requirements:
Measurement Model: Classical
License Type: Freeware
Documentation:

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covLCA

Author: Aurelie Bertrand and Christian M. Hafner
Contact: https://cran.r-project.org/web/packages/covLCA/index.html
Description: covLCA: Latent Class Models with Covariate Effects on Underlying and Measured Variables. Estimation of latent class models with covariate effects on underlying and measured variables. The measured variables are dichotomous or polytomous, all with the same number of categories.
Analyses: Attitude Scaling
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manua, sample dataset

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ctsem

Author: Charles Driver, Manuel Voelkle, Han Oud, Trustees of Columbia Universi
Contact: https://cran.r-project.org/web/packages/ctsem/index.html
Description: ctsem: Continuous Time Structural Equation Modelling. Hierarchical continuous time state space modelling, for linear and nonlinear systems measured by continuous variables, with limited support for binary data. The subject specific dynamic system is modelled as a stochastic differential equation (SDE), measurement models are typically multivariate normal factor models. Using the original ctsem formulation based on OpenMx, described in the JSS paper Continuous Time Structural Equation Modeling with R Package ctsem, with updated version as CRAN vignette <https://cran.r-project.org/web/packages/ctsem/vignettes/ctsem.pdf> , linear mixed effects SDE's estimated via maximum likelihood and optimization are possible. Using the Stan based formulation, described in <https://www.researchgate.net/publication/310747987_Introduction_to_Hierarchical_Continuous_Time_Dynamic_Modelling_With_ctsem> , nonlinearity (state dependent parameters) and random effects on all parameters are possible, using either optimization (with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling. Priors may be used. For the conceptual overview of the hierarchical Bayesian linear SDE approach, see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>. Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> . Stan based functions are not available on 32 bit Windows systems at present.
Analyses: Factor/Latent Structure; Item & Test Analysis; Scaling; Scoring
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual sample datasets

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CTT

Author: John Willse
Contact: https://cran.r-project.org/web/packages/CTT
Description: This package can be used to perform a variety of tasks and analyses associated with classical test theory (CTT): score multiple-choice responses, perform reliability analyses, conduct item analyses, and transform scores onto different scales.
Analyses: Attitude Scaling
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: User manual in pdf

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CTTShiny

Author: William Kyle Hamilton, Atsushi Mizumoto
Contact: https://cran.r-project.org/web/packages/CTTShiny/index.html
Description: CTTShiny: Classical Test Theory via Shiny. Interactive shiny application for running classical test theory (item analysis).
Analyses: Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multilevel Data; Simulation/Resampling
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: user manual

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DFIT

Author: Nambury S. Raju, T. Chris Oshima & Allen H. Wolach
Contact: https://cran.r-project.org/web/packages/DFIT/
Description: DFIT8 is a powerful Windows application designed to perform differential item functioning (DIF) analyses utilizing the DFIT framework originally proposed by Raju, van der Linden, & Fleer (1995). DFIT is an advanced approach based on item response theory (IRT) that compares the item response functions for groups of examinees to determine if a test item is performing significantly different for one group.
Analyses: Multilevel Data
System Requirements: Windows or Mac
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: PDF manual

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DIFAS

Author: Randall D. Penfield
Contact: http://soe.uncg.edu/academics/departments/erm/erm-software/
Description: DIFAS: Differential Item Functioning Analysis System. Windows-based program that computes odds ratio estimates of differential item functioning, differential test functioning, and differential step functioning effects, along with associated tests of significance. This includes the Mantel-Haenszel common log-odds ratio, the Breslow-Day test of trend in odds ratio heterogenity, and Liu-Agresti cumulative common log-odds ratio, and the relevant generalizations to step-level analyses for polytomous items.
Analyses: Item & Test Analysis; Latent Class Models; Multilevel Data
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: A manual is available in PDF format free of charge

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DIFboost

Author: Gunther Schauberger
Contact: https://cran.r-project.org/web/packages/DIFboost/index.html
Description: DIFboost: Detection of Differential Item Functioning (DIF) in Rasch Models by Boosting Techniques. Performs detection of Differential Item Functioning using the method DIFboost as proposed in Schauberger and Tutz (2015): Detection of Differential item functioning in Rasch models by boosting techniques, British Journal of Mathematical and Statistical Psychology.
Analyses: Cognitive Diagnostic Models; Item & Test Analysis; Multidimensional Models
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Rasch
License Type: Open-Source (R)
Documentation: user manual

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DIFlasso

Author: Gunther Schauberger
Contact: https://cran.r-project.org/web/packages/DIFlasso/index.html
Description: DIFlasso: A Penalty Approach to Differential Item Functioning in Rasch Models. Performs DIFlasso, a method to detect DIF (Differential Item Functioning) in Rasch Models. It can handle settings with many variables and also metric variables.
Analyses: DIF; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Rasch
License Type: Open-Source (R)
Documentation: user manual

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DIF-Pack

Author: Stout, W.
Contact: https://psychometrics.onlinehelp.measuredprogress.org/tools/dif/
Description: The DIF-Pack includes both source code and executable code for SIBTEST, POLY-SIBTEST, and Crossing SIBTEST, which together can test variously scored items and bundles of items (a bundle viewed as a collection) for various kinds of DIF.
Analyses: DIF; Dimensionality
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Open-Source
Documentation: open source

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difR

Author: David Magis, Sebastien Beland, & Gille Raiche
Contact: https://cran.r-project.org/web/packages/difR
Description: The difR package contains several traditional methods to detect DIF in dichotomously scored items. Both uniform and non-uniform DIF effects can be detected, with methods relying upon item response models or not. Some methods deal with more than one focal group. Methods currently available are: TID, M-H, Standardization, Breslow-Day, logistic regression, Lord's chi-square, Raju's area, LR test.
Analyses: Generalizability
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: User manual in pdf

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DIFtree

Author: Moritz Berger
Contact: https://cran.r-project.org/web/packages/DIFtree/index.html
Description: DIFtree: Item Focussed Trees for the Identification of Items in Differential Item Functioning. Item focussed recursive partitioning for simultaneous selection of items and variables that induce Differential Item Functioning (DIF) in dichotomous or polytomous items.
Analyses: Latent Class Models
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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DIM-Pack

Author: Stout, W.
Contact: https://psychometrics.onlinehelp.measuredprogress.org/tools/dim/
Description: DIM-Pack provides tools for conducting statistical dimensionality analyses on assessments consisting of dichotomously scored tasks. Briefly, the DIMTEST hypothesis testing statistic can be used to determine if the test is unidimensional, and DETECT, and HCA/CCPROX can be used to describe whatever multidimensionality is suspected to be present.
Analyses: Factor/Latent Structure; Multidimensional Models; Multilevel Data; Simulation/Resampling; Validity
System Requirements: Windows
Measurement Model: Latent Structure
License Type: Open-Source
Documentation: open source

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dina

Author: Steven Andrew Culpepper, James Joseph Balamuta
Contact: https://cran.r-project.org/web/packages/dina/index.html
Description: dina: Bayesian Estimation of DINA Model. Estimate the Deterministic Input, Noisy And Gate (DINA) cognitive diagnostic model parameters using the Gibbs sampler described by Culpepper (2015)
Analyses: Multilevel Data; Simulation/Resampling
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, sample dataset

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elasticnet

Author: Hui Zou and Trevor Hastie
Contact: https://cran.r-project.org/web/packages/elasticnet/index.html
Description: elasticnet: Elastic-Net for Sparse Estimation and Sparse PCA. Provides functions for fitting the entire solution path of the Elastic-Net and also provides functions for estimating sparse Principal Components. The Lasso solution paths can be computed by the same function. First version: 2005-10.
Analyses: Interrater Reliability; Interrater Reliability
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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emIRT

Author: Kosuke Imai, James Lo, Jonathan Olmsted
Contact: https://cran.r-project.org/web/packages/emIRT/index.html
Description: emIRT: EM Algorithms for Estimating Item Response Theory Models. Various Expectation-Maximization (EM) algorithms are implemented for item response theory (IRT) models. The current implementation includes IRT models for binary and ordinal responses, along with dynamic and hierarchical IRT models with binary responses. The latter two models are derived and implemented using variational EM. Subsequent edits also include variational network and text scaling models.
Analyses: Dimensionality; Factor/Latent Structure; Simulation/Resampling
System Requirements: Windows, Mac, Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, datasets

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EQSIRT

Author: Eric Wu and Peter Bentler; Patrick Mair and Steven Reise
Contact: http://www.mvsoft.com/eqsirt10.htm
Description: EQSIRT - a comprehensive Item Response Theory computer program - was developed with funding by the U.S. National Cancer Institute through a Small Business Innovation Research (SBIR) grant motivated by NIH's Patient Reported Outcomes (PROMIS) initiative. Authors and contributors: EQSIRT was designed by Eric Wu and Peter Bentler, who developed EQS, a popular structural equations modeling program. It was developed with IRT experts Patrick Mair and Steven Reise. Coherent and creative statistical programming was directed by Sam He, and complex interfaces were directed by Guisuo Guo. EQSIRT has a complete model builder to simplify the building of reusable IRT commands. Like EQS, the program includes a full service data management and general statistics component for preliminary data screening. EQSIRT is transportable across Microsoft Windows, Apple's Mac OS X (10.6 or higher), and various Linux operating systems.
Analyses: Cognitive Diagnostic Models; Item & Test Analysis; Latent Class Models
System Requirements: Windows, Mac, Linux
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation: Unlimited technical support

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equate

Author: Anthony Albano
Contact: https://cran.r-project.org/web/packages/equate
Description: Contains methods for observed-score linking and equating under the single-group, equivalent-groups, and nonequivalent-groups with anchor test(s) designs. Equating types include identity, mean, linear, general linear, equipercentile, circle-arc, and composites of these. Equating methods include synthetic, nominal weights, Tucker, Levine observed score, Levine true score, Braun/Holland, frequency estimation, and chained equating. Plotting and summary methods, and methods for multivariate presmoothing and bootstrap error estimation are also provided.
Analyses: DIF; Equating; Item & Test Analysis; Scaling; Scoring
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: User manual in pdf

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equateIRT

Author: Michela Battauz
Contact: https://cran.r-project.org/web/packages/equateIRT
Description: This package computes direct, chain and average (bisector) equating coefficients with standard errors using IRT methods for dichotomous items. The IRT models included are the three-parameter logistic model, the two-parameter logistic model, the one-parameter logistic model and the Rasch model.
Analyses: DIF; Dimensionality; Factor/Latent Structure; Reliability; Scaling; Scoring; Simulation/Resampling; MCMC
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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equateMultiple

Author: Michela Battauz
Contact: https://cran.r-project.org/web/packages/equateMultiple/index.html
Description: equateMultiple: Equating of Multiple Forms. Equating of multiple forms using Item Response Theory (IRT) methods (Battauz M. (2017) <doi:10.1007/s11336-016-9517-x> and Haberman S. J. (2009)
Analyses: DIF
System Requirements: Windows, Linus, or OS
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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Equating Error

Author: B. A. Hanson & Y. Chien
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: Equating Error estimates bootstrap standard errors of linear equating and equipercentile equating under the random groups design.
Analyses: Equating
System Requirements: Windows, MAC
Measurement Model: Classical
License Type: Freeware
Documentation: Manual in PDF format

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eRm

Author: Patrick Mair, Reinhold Hatzinger, Marco J. Maier
Contact: https://cran.r-project.org/web/packages/eRm/index.html
Description: eRm fits Rasch models (RM), linear logistic test models (LLTM), rating scale model (RSM), linear rating scale models (LRSM), partial credit models (PCM), and linear partial credit models (LPCM). Missing values are allowed in the data matrix. Additional features are the ML estimation of the person parameters, Andersen's LR-test, Ponocny's exact tests, item-specific Wald test, itemfit and personfit statistics including infit and outfit measures, various ICC and related plots, automated stepwise item elimination, simulation module for various binary data matrices.
Analyses: Person Fit/Cheating
System Requirements: Windows, Linux or Mac
Measurement Model: Rasch
License Type: Open-Source (R)
Documentation: Mair, P., & Hatzinger, R. (2007). Journal of Stati

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esaBcv

Author: Art B. Owen, Jingshu Wang
Contact: https://cran.r-project.org/web/packages/esaBcv/index.html
Description: esaBcv: Estimate Number of Latent Factors and Factor Matrix for Factor Analysis. These functions estimate the latent factors of a given matrix, no matter it is high-dimensional or not. It tries to first estimate the number of factors using bi-cross-validation and then estimate the latent factor matrix and the noise variances. For more information about the method, see Art B. Owen and Jingshu Wang 2015 archived article on factor model (http://arxiv.org/abs/1503.03515).
Analyses: DIF; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models; Person Fit/Cheating; Rater Effects; Scoring
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, simulated dataset

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EstCRM

Author: Cengiz Zopluoglu
Contact: https://cran.r-project.org/web/packages/EstCRM/index.html
Description: EstCRM: Calibrating Parameters for the Samejima's Continuous IRT Model. Estimates item and person parameters for the Samejima's Continuous Response Model (CRM), computes item fit residual statistics, draws empirical 3D item category response curves, draws theoretical 3D item category response curves, and generates data under the CRM for simulation studies.
Analyses: Item & Test Analysis; Scaling; Scoring
System Requirements: Windows, Mac, Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, sample dataset

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ETIRM

Author: B. A. Hanson
Contact: http://www.openirt.com/b-a-h/software/cpp/etirm.html
Description: ETIRM is a set of C++ classes and functions that can be used in programs for estimating parameters of item response theory (IRT) models. Currently, the components of ETIRM can be used to compute parameter estimates for the three-parameter logistic model with multiple groups (multiple-group estimation). There are plans to add estimation of other IRT models to ETIRM, including models for polytomous items. ETIRM is distributed under the BSD License.
Analyses: Dimensionality; Factor/Latent Structure
System Requirements: Programs using ETIRM have been successfully compil
Measurement Model: IRT/Rasch
License Type: Open-Source
Documentation: Some documentation of the numerical algorithms use

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EXTENSION

Author: Brian O'Connor
Contact: https://people.ok.ubc.ca/brioconn/extension/extension.html
Description: Scale development using popular statistical software packages often produces results that are baffling or misunderstood by many users, which can lead to inappropriate substantive interpretations and item selection decisions. High internal consistencies do not indicate unidimensionality; item-total correlations are inflated because each item is correlated with its own error as well as the common variance among items; and the default number-of-eigenvalues-greater-than-one rule, followed by principal components analysis and varimax rotation, produces inflated loadings and the possible appearance of numerous uncorrelated factors for items that measure the same construct (Gorsuch, 1997a, 1997b). Concerned investigators may then neglect the higher order general factor in their data as they use misleading statistical output to trim items and fashion unidimensional scales. These problems can be circumvented in exploratory factor analysis by using more appropriate factor analytic procedures and by using extension analysis as the basis for adding items to scales. Extension analysis provides correlations between nonfactored items and the factors that exist in a set of core items. The extension item correlations are then used to decide which factor, if any, a prospective item belongs to. The decisions are unbiased because factors are defined without being influenced by the extension items. One can also examine correlations between extension items and any higher order factor(s) in the core items. The end result is a comprehensive, undisturbed, and informative picture of the correlational structure that exists in a set of core items and of the potential contribution and location of additional items to the structure.
Analyses: Cognitive Diagnostic Models; Dimensionality; Factor/Latent Structure; Item & Test Analysis; Latent Class Models; Multidimensional Models; Multilevel Data; Simulation/Resampling; Validity
System Requirements: SAS, SPSS, or MATLAB
Measurement Model: Latent Structure
License Type: Open-Source
Documentation:

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Facets

Author: J. M. Linacre
Contact: http://www.winsteps.com/facets.htm
Description: Facets is designed to handle really tough applications of unidimensional Rasch measurement. It constructs measures from complex data involving heterogeneous combinations of examinees, items, tasks, judges along with further measurement and structural facets. It is designed to handle flexibly combinations of items of different formats in one analysis. Item types include dichotomies, rating scales with up to 255 categories, Poisson counts and Bernoulli trials. Multiple different measurement models can be included in the same analysis, including paired-comparisons, rank- order, rating scales, partial credit and dichotomizations involving from 1 to 255 facets.
Analyses: Test Construction & Administration
System Requirements: Windows
Measurement Model: Rasch
License Type: Commercial
Documentation: student version; online manual; manual in PDF

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Factor 9.2

Author: Urbano Lorenzo-Seva & Pere J. Ferrando
Contact: http://psico.fcep.urv.cat/utilitats/factor/
Description: FACTOR 9.2 was developed for three reasons. First, exploratory factor analysis (FA) is still an active field of research although most recent developments have not been incorporated into available programs. Second, there is now renewed interest in semiconfirmatory (SC) solutions as suitable approaches to the complex structures are commonly found in item analysis (e.g., McDonald, 2000). Finally, some popular item response theory (IRT) models can be fitted as FA models by using an underlying-variables approach. A program incorporating developments along these lines was thought to be highly useful for practitioners.
Analyses: Item & Test Analysis; Scaling; Scoring; MCMC estimation
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: brief guide, technical reports

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faoutlier

Author: R. Philip Chalmers & David B. Flora
Contact: https://cran.r-project.org/web/packages/faoutlier/index.html
Description: The R (R Core Team, 2014) package faoutlier implements a number of case diagnostic measures, including robust Mahalanobis distances, model-based outliers obtained using two-step approximations, goodness of fit distances, likelihood distances, generalized Cook's distances, as well as a forward search procedure to iteratively locate clusters of influential cases.
Analyses: Dimensionality; Factor/Latent Structure; Item & Test Analysis
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: Help Pages and vignettes

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FastTEST PC

Author: Assessment Systems Corp.
Contact: https://assess.com/fasttest-secure-online-testing/
Description: PC/Windows item banker and test assembly system for easy and efficient creation of printed tests, surveys, and questionaires. Full support for dichotomous IRT models.
Analyses: Equating
System Requirements: Windows
Measurement Model: Utilities
License Type: Commercial
Documentation: 30-day trial copy; network licenses

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FitPMM

Author: Cengiz Zopluoglu, Jeffrey R. Haring, & Nidhi Kohli
Contact: https://cengiz.me/fitpmm.html
Description: An R Routine to Fit Finite Mixture of Piecewise Mixed-Effect Models With Unknown Random Knots. In the R routine, a piecewise regression model with an unknown knot is first fitted to each individual's data using the segmented package in R (Muggeo, 2008). Then, multiple start value sets are generated using the procedure outlined by Hipp and Bauer (2006) for the initial stage estimations to overcome the problem of possible local solutions in estimating growth mixture models. After the initial stage estimations for a number of start value sets are completed, the best sets are reestimated until a convergence criterion is met.
Analyses: Item & Test Analysis
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source
Documentation:

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flexMIRT

Author: L. Cai
Contact: https://vpgcentral.com/software/
Description: Vector Psychometric Group, LLC is pleased to offer their IRT software flexMIRT, a multilevel, multidimensional, and multiple group item response theory (IRT) software package for item analysis and test scoring. flexMIRT fits a variety of unidimensional and multidimensional item response theory models (also known as item factor analysis models) to single-level and multilevel data in any number of groups.
Analyses: Item & Test Analysis; Person Fit/Cheating; Rater Effects; Scaling
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation: trial version; free to students w academic license

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flirt

Author: Minjeong Jeon, Frank Rijmen, & Sophia Rabe-Hesketh
Contact: https://sites.google.com/site/arbormj/sofware/flirt
Description: This package provides a flexible framework for uni- and multi- dimensional explanatory item response theory modeling for binary and polytomous item responses. The flexibility stems from specifying IRT models as generalized linear and nonlinear mixed models (Rijmen, Tuerlinckx, DeBoeck, & Kuppens, 2003).
Analyses: Scoring; Test Construction & Administration
System Requirements: Windows & Matlab
Measurement Model: IRT/Rasch
License Type: Open-Source
Documentation: User manual in pdf

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G1

Author: Mushquash, C., & O'Connor, B. P.
Contact: https://people.ok.ubc.ca/brioconn/gtheory/gtheory.html
Description: The identification and reduction of measurement errors is a major challenge in psychological testing. Most investigators rely solely on classical test theory for assessing reliability, whereas most experts have long recommended using generalizability theory instead. One reason for the common neglect of generalizability theory is the absence analytic facilities for this purpose in popular statistical software packages. This article provides a brief introduction to generalizability theory, describes easy to use SPSS, SAS, and MATLAB programs for conducting the recommended analyses, and provides an illustrative example using data (N = 329) for the Rosenberg Self-Esteem Scale. Program output includes variance components, relative and absolute errors and generalizability coefficients, coefficients for D studies, and graphs of D study results.
Analyses: Dimensionality; Item & Test Analysis; Multidimensional Models
System Requirements: SPSS, SAS, MATLAB
Measurement Model: Classical
License Type: Open-Source
Documentation:

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GDINA

Author: Wenchao Ma, Jimmy de la Torre, Miguel Sorrel, Zhehan Jiang
Contact: https://cran.r-project.org/web/packages/GDINA/index.html
Description: GDINA: The Generalized DINA Model Framework. A set of psychometric tools for cognitive diagnosis modeling based on the generalized deterministic inputs, noisy and gate (G-DINA) model by de la Torre (2011) <doi:10.1007/s11336-011-9207-7> and its extensions, including the sequential G-DINA model by Ma and de la Torre (2016) <doi:10.1111/bmsp.12070> for polytomous responses, and the polytomous G-DINA model by Chen and de la Torre <doi:10.1177/0146621613479818> for polytomous attributes. Joint attribute distribution can be independent, saturated, higher-order, loglinear smoothed or structured. Q-matrix validation, item and model fit statistics, model comparison at test and item level and differential item functioning can also be conducted. A graphical user interface is also provided.
Analyses: Generalizability
System Requirements: Windows, Mac, Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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GENOVA

Author: R. L. Brennan and J. E. Crick
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: GENOVA is a ANSI FORTRAN computer program for univariate generalizability analyses with complete, balanced designs. It has both G study and D study capabilities.
Analyses: Attitude Scaling; DIF; Item & Test Analysis; Scaling; Scoring
System Requirements: Macintosh PowerPCs and DOS/Windows-based PCs
Measurement Model: Classical
License Type: Freeware
Documentation: Manual in PDF format

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GGUM

Author: Jorge N. Tendeiro, Sebastian Castro-Alvarez
Contact: https://cran.r-project.org/web/packages/GGUM/index.html
Description: GGUM: Generalized Graded Unfolding Model. An implementation of the generalized graded unfolding model (GGUM) in R, see Roberts, Donoghue, and Laughlin (2000) <doi:10.1177/01466216000241001>). It allows to simulate data sets based on the GGUM. It fits the GGUM and the GUM, and it retrieves item and person parameter estimates. Several plotting functions are available (item and test information functions; item and test characteristic curves; item category response curves). Additionally, there are some functions that facilitate the communication between R and 'GGUM2004'. Finally, a model-fit checking utility, MODFIT(), is also available.
Analyses: Attitude Scaling; Equating; Scaling
System Requirements: Windows, Mac, Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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GGUM2004

Author: Roberts, James
Contact: http://prdlab.gatech.edu/unfolding/freesoftware/
Description: GGUM2004 is a Windows-based program that estimates parameters in the generalized graded unfolding model (GGUM; Roberts, Donoghue, & Laughlin, 2000).
Analyses: Factor/Latent Structure; Item & Test Analysis; Latent Class Models; Multidimensional Models; Multilevel Data; Simulation/Resampling
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: PDF manual; worked examples

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GGUMLINK

Author: Roberts, James
Contact: http://prdlab.gatech.edu/unfolding/freesoftware/
Description: GGUMLINK is a Windows-based FORTRAN program that equates parameter estimates from the Generalized Graded Unfolding Model using a variety of methods (Roberts, AERA 2001 Conference Paper ). The program is suitable for equating parameter estimates derived from separate calibrations in which common (anchor) items are included in each calibration.
Analyses: Item & Test Analysis; Reliability; Scaling; Scoring
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: PDF manual; worked examples; users can join messag

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Gifi

Author: Patrick Mair, Jan De Leeuw, Patrick J. F. Groenen
Contact: https://cran.r-project.org/web/packages/Gifi/index.html
Description: Gifi: Multivariate Analysis with Optimal Scaling. Implements categorical principal component analysis ('PRINCALS'), multiple correspondence analysis ('HOMALS'), monotone regression analysis ('MORALS'). It replaces the 'homals' package.
Analyses: Scaling; Scoring
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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GLAMM

Author: Sophia Rabe-Hesketh, Anders Skrondal, and Andrew P
Contact: http://www.gllamm.org/
Description: GLLAMMs are a class of multilevel latent variable models for (multivariate) responses of mixed type including continuous responses, counts, duration/survival data, dichotomous, ordered and unordered categorical responses and rankings. The latent variables (common factors or random effects) can be assumed to be discrete or to have a multivariate normal distribution. Examples of models in this class are multilevel generalized linear models or generalized linear mixed models, multilevel factor or latent trait models, item response models, latent class models and multilevel structural equation models.
Analyses: Item & Test Analysis; Multilevel Data; Reliability
System Requirements: STATA
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: free manual, sample data, and worked examples

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GPCMlasso

Author: Gunther Schauberger
Contact: https://cran.r-project.org/web/packages/GPCMlasso/index.html
Description: GPCMlasso: Differential Item Functioning in Generalized Partial Credit Models. Provides a framework to detect Differential Item Functioning (DIF) in Generalized Partial Credit Models (GPCM) and special cases of the GPCM as proposed by Schauberger and Mair (2019) <doi:10.3758/s13428-019-01224-2>. A joint model is set up where DIF is explicitly parametrized and penalized likelihood estimation is used for parameter selection. The big advantage of the method called GPCMlasso is that several variables can be treated simultaneously and that both continuous and categorical variables can be used to detect DIF.
Analyses: Item & Test Analysis; Scoring; Simulation/Resampling
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, sample dataset

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gtheory

Author: Christopher T. Moore
Contact: https://cran.r-project.org/web/packages/gtheory/index.html
Description: gtheory: Apply Generalizability Theory with R. Estimates variance components, generalizability coefficients, universe scores, and standard errors when observed scores contain variation from one or more measurement facets (e.g., items and raters).
Analyses: Item & Test Analysis; Person Fit/Cheating
System Requirements: Windows, Mac, Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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HLM

Author: Anthony S. Bryk - University of Chicago; Stephen W
Contact: www.ssicentral.com
Description: HLM, Hierarchical Linear Modeling, allows for the analysis of models with two or three levels of nesting (i.e., multilevel analysis). Such nested models may be used to analyze growth and change within individuals; to study responses of persons in organizations such as schools, businesses, community, and religious groups; and to conduct meta-analysis of research results. The HLM program handles both hierarchical linear and nonlinear models. All models can easily be formulated within this Windows version, as HLM leads the user step-by-step through the specification of the model at the respective levels.
Analyses: Item & Test Analysis; Simulation/Resampling; General IRT concepts/graphics
System Requirements: Windows
Measurement Model: Statistical
License Type: Commercial
Documentation: user manual; student version

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HSGen

Author: Chris T. Han
Contact: http://www.hantest.net/hsgen
Description: HSGen is a simple computer program that generates examinees' scores (mostly on IRT scale) in a hierarchical structure (for example, students' scores within each school and/or within each school district). Users can specify a mean value for the highest level groups and standard deviations for each level. This software can handle up to 5 levels of data.
Analyses: Item & Test Analysis; Reliability; Scoring
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: user manual, sample data files

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ICL 1.0

Author: B. A. Hanson
Contact: http://www.b-a-h.com/software/irt/icl/index.html
Description: IRT Command Language (ICL) is a computer program that can perform single- or multiple-group estimation of the 1-, 2-, and 3-parameter logistic item response models for dichotomous items, and the partial credit model and generalized partial credit model for polytomous items.
Analyses: Simulation/Resampling; Test Construction & Administration
System Requirements: MS-DOS command prompt; runs in Windows 95/NT, Maci
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: ICL manual is available in HTML and PDF formats

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immer

Author: Alexander Robitzsch, Jan Steinfeld
Contact: https://cran.r-project.org/web/packages/immer/index.html
Description: immer: Item Response Models for Multiple Ratings. Implements some item response models for multiple ratings, including the hierarchical rater model, conditional maximum likelihood estimation of linear logistic partial credit model and a wrapper function to the commercial FACETS program. See Robitzsch and Steinfeld (2018) for a description of the functionality of the package. See Wang, Su & Qiu (2014; <doi:10.1111/jedm.12045>) for an overview of modeling alternatives.
Analyses: Equating
System Requirements: Windows, Mac, Linux
Measurement Model: Rasch
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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Integrity

Author: Castle Rock Research Corp.
Contact: https://integrity.castlerockresearch.com/
Description: Integrity is a secure online application designed to provide detailed information regarding the performance of multiple-choice test items and to conduct advanced collusion detection analyses.
Analyses: DIF; Item & Test Analysis
System Requirements: Windows, MAC
Measurement Model: Utilities
License Type: Commercial
Documentation:

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irr

Author: M. Gamer, J. Lemon, I. Fellows, T. Wenzel-Larsen
Contact: https://cran.r-project.org/web/packages/irr
Description: Coefficients of reliability and agreement for various levels of data. Open source (GPL 2) written in the R statistical language. May run without modification in the S-PLUS statistical language.
Analyses: Equating
System Requirements: as for the R statistical language
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: Help pages in three formats (test, HTML, Latex) an

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IRT Scoring

Author: Assessment Systems Corp.
Contact: http://www.assess.com/irt-scoring-spreadsheet/
Description: Item Response Theory (IRT) is the measurement paradigm used by the majority of high-stakes testing programs across the world. Because it is very mathematically and conceptually complex, it still remains underutilized. If you are new to IRT, one of the most important concepts to learn is scoring algorithms. The IRT Scoring Spreadsheet helps you learn this process interactively, by letting you enter various item parameters and student responses, then watch the likelihood functions and theta estimates change in real time.
Analyses: Equating
System Requirements:
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation:

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irtDemo

Author: Metin Bulus & Wes Bonifay
Contact: https://cran.r-project.org/web/packages/irtDemo/index.html
Description: irtDemo: Item Response Theory Demo Collection. Includes a collection of shiny applications to demonstrate or to explore fundamental item response theory (IRT) concepts such as estimation, scoring, and multidimensional IRT models.
Analyses: Item & Test Analysis; Multidimensional Models; Scoring
System Requirements: Windows, Mac, Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation:

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IRTEQ

Author: Kyung (Chris) T. Han
Contact: http://www.hantest.net/irteq
Description: IRTEQ is a freeware Windows GUI application that implements IRT scaling and equating developed by Kyung (Chris) T. Han. It implements IRT scaling/equating methods that are widely used with an anchor test design (the “Non-Equivalent Groups Anchor Test”): Mean/Mean, Mean/Sigma, Robust Mean/Sigma, and TCC methods. For TCC methods, IRTEQ provides the user with the option to choose various score distributions for incorporation into the loss function. IRTEQ supports various popular unidimensional IRT models: Logistic models for dichotomous responses (with 1, 2, or 3 parameters) and the Generalized Partial Credit Model (GPCM) (including Partial Credit Model (PCM), which is a special case of GPCM) and Graded Response Model (GRM) for polytomous responses. IRTEQ can also equate test scores on the scale of a test to the scale of another test using IRT true score equating.
Analyses: Equating; Multidimensional Models
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: user's manual and example data

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IRT-Lab

Author: Randall D. Penfield
Contact: http://soe.uncg.edu/academics/departments/erm/erm-software/
Description: IRT-Lab is a program intended to be used in teaching and understanding IRT concepts. The program allows the user to view the item characteristic curves for specified parameterizations of numerous IRT and Rasch models (dichotomous and polytomous), as well as view the associated item and test information functions, and likelihood functions associated with maximum likelihood estimation of ability and item parameter estimation. In addition, IRT-Lab can generate simulated responses to a specified group of items.
Analyses: DIF; Dimensionality; Equating; Latent Class Models; Multidimensional Models; Multilevel Data; Simulation/Resampling
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: A manual in PDF format is available free of charge

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irtoys

Author: Ivailo Partchev, Gunter Maris, Tamaki Hattori
Contact: https://cran.r-project.org/web/packages/irtoys/index.html
Description: irtoys: A Collection of Functions Related to Item Response Theory (IRT). A collection of functions useful in learning and practicing IRT, which can be combined into larger programs. Provides basic CTT analysis, a simple common interface to the estimation of item parameters in IRT models for binary responses with three different programs (ICL, BILOG-MG, and ltm), ability estimation (MLE, BME, EAP, WLE, plausible values), item and person fit statistics, scaling methods (MM, MS, Stocking-Lord, and the complete Hebaera method), and a rich array of parametric and non-parametric (kernel) plots. Estimates and plots Haberman's interaction model when all items are dichotomously scored.
Analyses: Item & Test Analysis; Scaling; Scoring; nonparametric IRT
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, sample dataset

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IRTPRO

Author: Li Cai, David Thissen & Stephen du Toit
Contact: https://vpgcentral.com/software/
Description: IRTPRO is an advanced application for item calibration and test scoring using item response theory (IRT). It comes with an intuitive graphical user interface and offers built-in production quality IRT graphics. Suitable for educators, students, researchers, and assessment organizations, IRTPRO™ has enjoyed increasingly wide usage in the educational, psychological, social, and health sciences.
Analyses: Factor/Latent Structure; Multidimensional Models; Simulation/Resampling
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation: User manual in pdf student version

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irtProb

Author: Gilles Raiche
Contact: https://cran.r-project.org/web/packages/irtProb/index.html
Description: The irtProb R package was mainly developped to compute probability distributions in the context of Item Response Theory (IRT). Actually two families of models are taken into account. The first is the family of 1, 2, 3 and 4 parameters logistic functions. The second is a new multidimensional logistic family adding of 1, 2, 3 and 4 person parameters. Some utilitarian functions are also available. So it is possible to generate response patterns with each family of item response models and other functions are also available to do conversion of item parameters between classical test theory and item response theory (2PL). Maximum likelihood and Maximum a posteriori estimation function of the multidimensional person parameters are also available.
Analyses: Scoring
System Requirements: Any system running R
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: A manual and a vignette are available with the pac

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IRTShiny

Author: W. Kyle Hamilton, Atsushi Mizumoto
Contact: https://cran.r-project.org/web/packages/IRTShiny/index.html
Description: IRTShiny: Item Response Theory via Shiny. Interactive shiny application for running Item Response Theory analysis. Provides graphics for characteristic and information curves.
Analyses: Generalizability
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation:

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ITEMAN

Author: Assessment Systems Corp.
Contact: https://assess.com/iteman/
Description: Iteman represents the cutting edge in psychometric analysis software, giving you the power to create professional psychometric reports with the click of a mouse. Iteman produces a comprehensive classical test theory analysis of your exam, including a quantile plot and detailed table of statistics for each item, but its user-friendly interface makes it accessible to novices and experts alike.
Analyses: DIF; Differential test functioning and differential step function
System Requirements: Windows
Measurement Model: Classical
License Type: Commercial
Documentation: manual in PDF; demo version

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IzstarMix

Author: Sandip Sinharay
Contact: ssinharay@pacificmetrics.com
Description: In a report for the Council of Chief State School Officers, Olson and Fremer (2013) recommended the use of person-fit assessment, in addition to other methods, to detect irregularities in answering behavior of the test takers. lzstarMix is a function written in R (R Core Team, 2015) to compute the lz statistic for mixed-format tests (Drasgow, Levine, & Williams, 1985; Sinharay, 2015b). The function also computes the lz statistic for mixed-format tests that was recently suggested by Sinharay (2015a). The null distribution of lz is generally much closer than that of lz to the standard normal distribution for mixed-format tests. The function lzstarMix currently works when the dichotomous items are modeled using the three-parameter logistic (3PL) model, and the polytomous items are modeled using the generalized partial credit model (GPCM; Muraki, 1992). The input to the function consists of the item-parameter estimates, and the item scores and estimated abilities (maximum likelihood estimate or weighted likelihood estimates) of several examinees. The output are lz and lz for the examinees. The function can be used for tests that include only dichotomous items, in which case lz for mixed-format tests (Sinharay, 2015a) becomes identical to lz for dichotomous items (Snijders, 2001), or only polytomous items.
Analyses: Attitude Scaling; DIF; Item & Test Analysis; Latent Class Models; Person Fit/Cheating; Reliability; Simulation/Resampling; Test Construction & Administration
System Requirements: Windows; Mac; Linux
Measurement Model: IRT/Rasch
License Type: Open-Source
Documentation: User manual, sample data sets

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jMetrik

Author: J. Patrick Meyer
Contact: http://www.itemanalysis.com/
Description: jMetrik is a free and open source computer program for psychometric analysis. (See who is using jMetrik.) It features a user-friendly interface, integrated database, and a variety of statistical procedures and charts. The interface is intuitive and easy to learn. It also scales to the experience of the user. New users can quickly learn to implement psychometric procedures though point-and-click menus. Experienced users can take advantage of the jMetrik command structure and write command files for executing an analysis.
Analyses: Equating; Item & Test Analysis; Reliability
System Requirements: Windows, Mac, Linux
Measurement Model: Classical
License Type: Open-Source
Documentation: online technical support

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kcirt

Author: Dave Zes, Jimmy Lewis, Dana Landis
Contact: https://cran.r-project.org/web/packages/kcirt/index.html
Description: kcirt: k-Cube Thurstonian IRT Models. Create, Simulate, Fit, Solve k-Cube Thurstonian IRT Models
Analyses: DIF; Item & Test Analysis; Person Fit/Cheating; Rater Effects; Scaling; Scoring
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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kequate

Author: Bjorn Andersson, Keny Branberg, & Marie Wiberg
Contact: https://cran.r-project.org/web/packages/kequate
Description: The kernel equating technique for equating test scores is implemented, supporting the Equivalent Groups (EG), Single Group (SG), Counterbalanced (CB), Non-Equivalent groups with Anchor Test Chain Equating (NEAT CE), Non-Equivalent groups with Anchor Test Post-Stratification Equating (NEAT PSE) and Non-Equivalent groups with Covariates (NEC) designs. Support for three types of kernels is provided: Gaussian, logistic and uniform. Standard errors of equating and standard errors of the difference between two equating functions are provided for all designs and kernels. Also included are functions aiding the search for a proper log-linear pre-smoothing model and the ability to use Item Response Theory Observed Score Equating (IRT-OSE) in the Kernel Equating framework.
Analyses: DIF; Equating; Item & Test Analysis; Scoring
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: User manual in pdf

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Latent Gold

Author: Statistical Innovations
Contact: https://www.statisticalinnovations.com/latent-gold-5-1
Description: Latent GOLD is a powerful latent class and finite mixture program with a very user-friendly point-and-click interface (GUI). Two add-on options are available to extend the basic version of the program. The Advanced/Syntax add-on enables more control for advanced users via use of a Syntax command language including intuitive LG-equations. This add-on also contains more advanced GUI modeling features such as Latent (Hidden) Markov and Multilevel models. The Choice add-on allows estimation of discrete choice models via the point-and-click interface. When obtaining both the Choice and the Advanced/Syntax add-on, various advanced choice models can be estimated and the Syntax can also be used to further the customize discrete choice models.
Analyses: Multidimensional Models; Simulation/Resampling; Test Construction & Administration
System Requirements: Windows
Measurement Model: Latent Structure
License Type: Commercial
Documentation:

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lavaan

Author: Yves Rosseel et al.
Contact: https://cran.r-project.org/web/packages/lavaan
Description: Fit a variety of latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models.
Analyses: Dimensionality; Factor/Latent Structure; Item & Test Analysis
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: User manual in pdf

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LEGS

Author: R. L. Brennan
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: LEGS conducts linear and equipercentile linking.
Analyses: Dimensionality; Item & Test Analysis; Multidimensional Models
System Requirements: Windows , MAC
Measurement Model: Classical
License Type: Freeware
Documentation: Manual in PDF format

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Lertap5

Author: Larry Nelson
Contact: https://lertap5.com/store/index.html?about_the_author.htm
Description: Lertap is a software system used to process and analyze data collected from quizzes, exams, tests, and surveys. Lertap is an acronym for the Laboratory of Educational Research Test Analysis Package. It dates way back to 1973. Lertap 5, the latest genre, works with Microsoft's spreadsheet program, Excel. There are versions for Macintosh and Windows computers. Lertap 5's forte is item analysis and test scoring. The majority of the statistics it produces are solidly based on CTT, classical test theory. It will handle polytomous cognitive and affective items (such as rating scales), with extensive support for partial-credit item scoring. A virtual cornucopia of charts and graphs is a salient feature of Lertap 5. Lertap is free for students to use.
Analyses: DIF
System Requirements: Excel and Windows or Mac
Measurement Model: Classical
License Type: Commercial
Documentation: manual, sample data, online help

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LinkMIRT

Author: Lihua Yao
Contact: http://www.bmirt.com/6271.html
Description: LinkMIRT (Yao, 2009), Linking Multivariate Item Response Theory, is a computer program that links two sets of item parameters by matching test response function, mean/mean, and mean/sigma in the multidimensional frame work.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: User manual in pdf

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LISREL

Author: Karl Jöreskog, Dag Sörbom
Contact: https://ssicentral.com/index.php/products/lisrel/
Description: During the last forty-five years, the LISREL model, methods and software have become synonymous with structural equation modeling (SEM). Today, however, LISREL is no longer limited to SEM. LISREL 10 includes the 64-bit statistical applications LISREL, PRELIS, MULTILEV, SURVEYGLIM and MAPGLIM. LISREL for structural equation modeling. PRELIS for data manipulations and basic statistical analyses. MULTILEV for hierarchical linear and non-linear modeling. SURVEYGLIM for generalized linear modeling. MAPGLIM for generalized linear modeling for multilevel data.
Analyses: Generalizability
System Requirements: Windows , Mac
Measurement Model: Latent Structure
License Type: Commercial
Documentation: manuals; user's guide in PDF; student/demo version

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lme4

Author: Douglas Bates, Martin Maechler, Ben Bolker, Steven Walker, Rune Haubo
Contact: https://cran.r-project.org/web/packages/lme4/index.html
Description: lme4: Linear Mixed-Effects Models using 'Eigen' and S4. Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' glue.
Analyses: DIF; Equating; Item & Test Analysis; Reliability; Scaling; Scoring; Rasch models
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Rasch
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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lordif

Author: Seung W. Choi, with contributions from Laura E. Gibbons and Paul K. Cr
Contact: https://cran.r-project.org/web/packages/lordif/index.html
Description: lordif: Logistic Ordinal Regression Differential Item Functioning using IRT. Analysis of Differential Item Functioning (DIF) for dichotomous and polytomous items using an iterative hybrid of ordinal logistic regression and item response theory (IRT).
Analyses: Dimensionality; Factor/Latent Structure; Item & Test Analysis; Latent Class Models; Multidimensional Models
System Requirements: Windows, Mac, Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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lslx

Author: Po-Hsien Huang, Wen-Hsin Hu
Contact: https://cran.r-project.org/web/packages/lslx/index.html
Description: lslx: Semi-Confirmatory Structural Equation Modeling via Penalized Likelihood or Least Squares. Fits semi-confirmatory structural equation modeling (SEM) via penalized likelihood (PL) or penalized least squares (PLS).
Analyses: DIF
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual

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ltm

Author: Dimitris Rizopoulos
Contact: https://github.com/drizopoulos/ltm
Description: Analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach. It includes the Rasch, the Two-Parameter Logistic, the Birnbaum's Three-Parameter, the Graded Response, and the Generalized Partial Credit Models.
Analyses: Item & Test Analysis
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source
Documentation: user manual, sample data

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MAT

Author: Seung W. Choi & David R. King
Contact: https://cran.r-project.org/web/packages/MAT/
Description: Multidimensional adaptive testing (MAT) is ideal for testing situations that require the estimation of two or more distinct, albeit correlated latent abilities. MAT offers a number of advantages over unidimensional adaptive testing, such as more adequate coverage of content (Segall,1996), increased measurement efficiency for variable-length tests (Segall, 1996), and increased measurement precision for fixed-length tests (Wang, Chen, & Cheng, 2004). Simulation of MAT on both empirical and generated data is useful for developing computerized adaptive testing (CAT) systems and for teaching the principles of MAT.
Analyses: diagnostics from MCMC output
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: guide in pdf

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mcIRT

Author: Manuel Reif
Contact: https://cran.r-project.org/web/packages/mcIRT
Description: This package provides functions to estimate two popular IRT-models: The Nominal Response Model (Bock 1972) and the quite recently developed Nested Logit Model (Suh & Bolt 2010). These are two models to examine multiple-choice items and other multicategorial response formats. It is possible to estimate multiple group models and to model interaction effects to examine Differential Item Functioning. Each model has a full accessible design matrix which allows the user to manipulate and set up his own weighting scheme and his own constraints. One application could be modeling and testing item properties by means of customizing the design matrix and estimating an explanatory Nominal Response Model or an explanatory Nested Logit Model.
Analyses: Item & Test Analysis
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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MCMC GGUM

Author: Wei Wang, Jimmy de la Torre, & Fritz Drasgow
Contact: computationalpsychology.org/resources/
Description: The MCMC GGUM computer program employs the Metropolis-Within-Gibbs algorithm (Hastings, 1970; Metropolis, Rosenbluth, Rosenbluth, Teller, & Teller, 1953) and estimates the item and person parameters simultaneously. This program is capable of calibrating data sets with up to 10 response categories, and, theoretically, with no limit on the number of items and respondents. This program can also handle missing values in the data. In addition, the MCMC GGUM computer program allows users to adjust the distributions of priors, which is an important feature that is not supported in GGUM2004.
Analyses: Equating; Scaling
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: user manual, sample data and syntax

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MCMC Z-G

Author: Wei Wang, Philseok Lee, Seang-Hwane Joo, & Stephen Stark
Contact: computationalpsychology.org/resources/
Description: The MCMC Z-G computer program estimates the Zinnes Griggs (Z-G) item response theory model (Z-G IRT; Zinnes & Griggs, 1974). Contrast to the GGUM2004 (Roberts, Fang, Cui, & Y. Wang, 2006) and the MCMC GGUM (W. Wang, de la Torre, & Drasgow, 2014) that calibrate the single-stimulus response data, the MCMC Z-G calibrate response data from the forced-choice measurement formats, which potentially address the response style and bias problem that are typically caused by the popular single-stimulus measurement formats. Similar to the MCMC GGUM (Wang, et al., 2014), the MCMC Z-G computer program also employs the Metropolis-within-Gibbs algorithm based Markov chain Monte Carlo method (Hastings, 1970; Metropolis, A. Rosenbluth, M. Rosenbluth, A. Teller, & E. Teller, 1953) and estimates both the item and person parameters, and it can handle missing values in the data.
Analyses: Simulation/Resampling; Test Construction & Administration; CAT
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: User manual

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MCMCglmm

Author: Jarrod Hadfield
Contact: https://cran.r-project.org/web/packages/MCMCglmm/index.html
Description: MCMCglmm: MCMC Generalised Linear Mixed Models. MCMCglmm is a package for fitting Generalised Linear Mixed Models using Markov chain MonteCarlo techniques (Hadfield 2009). Most commonly used distributions like the normal and the Pois-son are supported together with some useful but less popular ones like the zero-inflated Poisson andthe multinomial. Missing values and left, right and interval censoring are accommodated for alltraits. The package also supports multi-trait models where the multiple responses can follow differ-ent types of distribution. The package allows various residual and random-effect variance structures to be specified including heterogeneous variances, unstructured covariance matrices and random re-gression (e.g. random slope models). Three special types of variance structure that can be specifiedare those associated with pedigrees (animal models), phylogenies (the comparative method) andmeasurement error (meta-analysis).
Analyses: Factor/Latent Structure; Latent Class Models; Multidimensional Models; Reliability; Simulation/Resampling; Validity
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Rasch
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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mdltm GDM

Author: Matthias von Davier
Contact: http://www.von-davier.com/
Description: A graphical user interface and estimation algorithm for the general diagnostic model. Research license (contact author for details and to obtain a license agreement). The software provides marginal maximum likelihood estimates obtained using customary EM methods. This software is suitable for data from large-scale assessment programs like PISA, NAEP, IALS, or TIMSS. Estimates can be obtained for a variety of models: IRT , multivariate IRT, latent class, diagnostic, mixture distribution, multidimensional mixture IRT, mixture diagnostic, multiple group, and growth mixture models. mdltm can handle the following data types: dichotomous / polytomous response data, matrix samples (data missing by design and at random), weighted data, and grouped data (multiple-population multiple-group IRT models and non-parametric hierarchical LCA and mixture IRT).
Analyses: Dimensionality; Factor/Latent Structure
System Requirements: Windows (GUI and estimation core software) Linux or Mac OSX
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: Draft manual, examples

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mGENOVA

Author: R. L. Brennan
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: mGENOVA is an ANSI C computer program for multivariate generalizability analyses for a restricted class of designs. For these designs, the program has both G study and D study capabilities.
Analyses: Cognitive Diagnostic Models; DIF; Item & Test Analysis; Latent Class Models; Multidimensional Models; Multilevel Data; Person Fit/Cheating; Scaling
System Requirements: Mac, Windows
Measurement Model: Classical
License Type: Freeware
Documentation: Manual in PDF format

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mirt

Author: Phil Chalmers, Joshua Pritikin, Alexander Robitsch, & Mateusz Zoltak
Contact: https://cran.r-project.org/web/packages/mirt
Description: Analysis of dichotomous and polytomous response data using unidimensional and multidimensional latent trait models under the Item Response Theory paradigm. Exploratory and confirmatory models can be estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier analyses are available for modeling item testlets. Multiple group analysis and mixed effects designs also are available for detecting differential item functioning and modelling item and person covariates.
Analyses: Item & Test Analysis; IRT model fit
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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mirtCAT

Author: Phil Chalmers
Contact: https://cran.r-project.org/web/packages/mirtCAT/index.html
Description: mirtCAT: Computerized Adaptive Testing with Multidimensional Item Response Theory. Provides tools to generate an HTML interface for creating adaptive and non-adaptive educational and psychological tests using the shiny package (Chalmers (2016) <doi:10.18637/jss.v071.i05>). Suitable for applying unidimensional and multidimensional computerized adaptive tests (CAT) using item response theory methodology and for creating simple questionnaires forms to collect response data directly in R. Additionally, optimal test designs (e.g., shadow testing) are supported for tests which contain a large number of item selection constraints. Finally, package contains tools useful for performing Monte Carlo simulations for studying the behavior of computerized adaptive test banks.
Analyses: Dimensionality; Factor/Latent Structure; Item & Test Analysis; Reliability; Simulation/Resampling
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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mirtjml

Author: Siliang Zhang, Yunxiao Chen, Xiaoou Li
Contact: https://cran.r-project.org/web/packages/mirtjml/index.html
Description: Provides constrained joint maximum likelihood estimation algorithms for item factor analysis (IFA) based on multidimensional item response theory models. So far, we provide functions for exploratory and confirmatory IFA based on the multidimensional two parameter logistic (M2PL) model for binary response data. Comparing with traditional estimation methods for IFA, the methods implemented in this package scale better to data with large numbers of respondents, items, and latent factors. The computation is facilitated by multiprocessing 'OpenMP' API. For more information, please refer to: 1. Chen, Y., Li, X., & Zhang, S. (2018). Joint Maximum Likelihood Estimation for High-Dimensional Exploratory Item Factor Analysis. Psychometrika, 1-23.
Analyses: Interrater Reliability; Interrater Reliability; Rater Effects; Reliability; Sample size calculation for reliability
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, simulated dataset

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Mixed-Up Suite

Author: Donald Hedeker and Robert D. Gibbons
Contact: https://hedeker.people.uic.edu/mix.html
Description: Mixed-Up is a suite of program: MIXOR, MIXREG, MIXNO, MIXPREG. It including mixed-effects linear regression, mixed-effects logistic regression for nominal or ordinal outcomes, mixed-effects probit regression for ordinal outcomes, mixed-effects Poisson regression, and mixed-effects grouped-time survival analysis.These models are also called multilevel models, hierarchical linear models, random-effects models, and random coefficients models, to name a few.
Analyses: Attitude Scaling; Person Fit/Cheating; Simulation/Resampling
System Requirements: Windows
Measurement Model: Statistical
License Type: Freeware
Documentation: PDF manuals and user guides; sample data and worke

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mixRasch

Author: John T. Willse
Contact: https://cran.r-project.org/web/packages/mixrasch
Description: The included function will estimate a mixture Rasch model using joint maximum likelihood esti-mation (JMLE). The estimation is based on a mixture partial credit model. Step parameters can be constrained to estimate a mixture rating scale model. Estimating a model with only one latent class accomplishes a standard Rasch analysis with JMLE.
Analyses: Attitude Scaling; Dimensionality; Factor/Latent Structure; Generalizability; Interrater Reliability; Interrater Reliability; Item & Test Analysis; Multidimensional Models; Reliability; Scaling; Scoring; Simulation/Resampling
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User Manual

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MLCIRTwithin

Author: Francesco Bartolucci, Silvia Bacci
Contact: https://cran.r-project.org/web/packages/MLCIRTwithin/index.html
Description: MLCIRTwithin: Latent Class Item Response Theory (LC-IRT) Models under Within-Item Multidimensionality. Framework for the Item Response Theory analysis of dichotomous and ordinal polytomous outcomes under the assumption of within-item multidimensionality and discreteness of the latent traits. The fitting algorithms allow for missing responses and for different item parametrizations and are based on the Expectation-Maximization paradigm. Individual covariates affecting the class weights may be included in the new version together with possibility of constraints on all model parameters.
Analyses: Factor/Latent Structure; Multidimensional Models; Person Fit/Cheating; Simulation/Resampling
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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MLwiN

Author: The Centre for Multilevel Modelling (CMM), Univers
Contact: http://www.cmm.bristol.ac.uk/MLwiN/
Description: Multilevel modelling has rapidly become established as the appropriate tool for modelling data with complex hierarchical structures. An important feature of MLwiN is its graphical interfaces. These allow the user easily to set up, fit and manipulate models. There are windows for data manipulation, plotting, viewing the progress of iterations etc. Predictions from fitted models can be specified directly using standard statistical notation with direct links to various kinds of derived graphs, which are automatically updated as model parameters change. Likewise, posterior residual estimates and functions of them can be linked directly to graphs, for example for model diagnostics. Markov Chain Monte Carlo (MCMC) Bayesian modelling is incorporated with detailed visual diagnostics. Parametric nd non-parametric bootstrapping is available and an iterated bootstrap has been implemented for unbiased estimation with multilevel generalised linear models.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models; Simulation/Resampling
System Requirements: Windows
Measurement Model: Statistical
License Type: Commercial
Documentation: free training version; free for UK academics; 30-d

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MOKKEN

Author: L. Andries van der Ark, Letty Koopman
Contact: https://cran.r-project.org/web/packages/mokken/index.html
Description: Mokken scale analysis (Mokken, 1971; Sijtsma and Molenaar, 2002) is a scaling procedure for both dichotomous and polytomous items. It consists of an item selection algorithm to partition a set of items into Mokken scales and several methods to check the assumptions of two nonparametric item response theory models: the monotone homogeneity model and the double monotonicity model. The output of this R-package resembles the output of the stand-alone program MSP (Molenaar and Sijtsma, 2000).
Analyses: Dimensionality; Factor/Latent Structure; Item & Test Analysis; Multidimensional Models; Simulation/Resampling
System Requirements: Windows, R
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: open source

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MPlus

Author: Bengt O. Muthén, Linda Muthén
Contact: http://www.statmodel.com/
Description: Mplus is a statistical modeling program that provides researchers with a flexible tool to analyze their data. Mplus offers researchers a wide choice of models, estimators, and algorithms in a program that has an easy-to-use interface and graphical displays of data and analysis results. The Mplus modeling framework draws on the unifying theme of latent variables. The generality of the Mplus modeling framework comes from the unique use of both continuous and categorical latent variables.
Analyses: Interrater Reliability; Interrater Reliability; Item & Test Analysis; Multilevel Data; Reliability; Meta-analysis; classical utility analysis; various correlati
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Latent Structure
License Type: Commercial
Documentation: user manual, sample data and syntax

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mRm

Author: David Preinerstorfer
Contact: https://cran.r-project.org/web/packages/mRm/index.html
Description: mRm: An R Package for Conditional Maximum Likelihood Estimation in Mixed Rasch Models. Conditional maximum likelihood estimation via the EM algorithm and information-criterion-based model selection in binary mixed Rasch models.
Analyses: Item & Test Analysis
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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MSTGen

Author: Chris T. Han
Contact: http://www.hantest.net/mstgen/
Description: Multistage testing, or MST, was developed as an alternative to computerized adaptive testing (CAT) for applications in which it is preferable to administer a test at the level of item sets (i.e., modules). MSTGen, a new MST simulation software tool, was developed to serve various purposes ranging from fundamental MST research to technical MST program evaluations. The new CAT simulation software tool supports both traditional MST functioning (MST by routing to preassembled modules after each stage; Luecht & Nungester, 1998) and new MST methods (e.g., MST by shaping a module for each stage; Han & Guo, 2012). It offers a variety of test administration environments and a user-friendly graphical interface.
Analyses: Attitude Scaling
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: user manual, sample data files

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MultiLCIRT

Author: Francesco Bartolucci, Silvia Bacci, Michela Gnaldi
Contact: https://cran.r-project.org/web/packages/MultiLCIRT/index.html
Description: MultiLCIRT: Multidimensional Latent Class Item Response Theory Models. Framework for the Item Response Theory analysis of dichotomous and ordinal polytomous outcomes under the assumption of multidimensionality and discreteness of the latent traits. The fitting algorithms allow for missing responses and for different item parameterizations and are based on the Expectation-Maximization paradigm. Individual covariates affecting the class weights may be included in the new version (since 2.1).
Analyses: Scaling; Scoring
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual, sample dataset

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nFactors

Author: Gilles Raiche, David Magis
Contact: https://cran.r-project.org/web/packages/nFactors/index.html
Description: An R package was developed to implement diverse previously proposed numerical strategies to determine the number of components/factors to retain in PCA or PA. The considered strategies can be classified into three categories: heuristics, likelihood ratio tests and simulations. The package also implements complementary graphical and utilitarian functions: Accordingly, to palliate convergence problems with some factor analysis estimations functions implemented in R, two simpler and less precise estimations methods are available: iterated or not principal axis analysis. Also, functions useful to design simulation of principal components and factor structure are available.
Analyses: Factor/Latent Structure; Multidimensional Models
System Requirements: Windows, Mac, Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: A manual and a vignette are available with the pac

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nlsem

Author: Nora Umbach, Katharina Naumann, David Hoppe, Holger Brandt, Augustin K
Contact: https://cran.r-project.org/web/packages/nlsem/index.html
Description: nlsem: Fitting Structural Equation Mixture Models. Estimation of structural equation models with nonlinear effects and underlying nonnormal distributions.
Analyses: Item & Test Analysis; Scoring; Simulation/Resampling; Test Construction & Administration
System Requirements: Windows, Mac OS, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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NOHARM

Author: C. Fraser & R. P. McDonald
Contact: http://noharm.software.informer.com/
Description: A Windows program for fitting both unidimensional and multidimensional normal ogive models of latent trait theory.
Analyses: Reliability; Test Construction & Administration
System Requirements: Windows, online version
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: users guide; sample input/output files

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nsprcomp

Author: Christian, R Core team
Contact: https://cran.r-project.org/web/packages/nsprcomp/index.html
Description: nsprcomp: Non-Negative and Sparse PCA. Two methods for performing a constrained principal component analysis (PCA), where non-negativity and/or sparsity constraints are enforced on the principal axes (PAs). The function 'nsprcomp' computes one principal component (PC) after the other. Each PA is optimized such that the corresponding PC has maximum additional variance not explained by the previous components. In contrast, the function 'nscumcomp' jointly computes all PCs such that the cumulative variance is maximal. Both functions have the same interface as the 'prcomp' function from the 'stats' package (plus some extra parameters), and both return the result of the analysis as an object of class 'nsprcomp', which inherits from 'prcomp'. See <https://sigg-iten.ch/learningbits/2013/05/27/nsprcomp-is-on-cran/> and Sigg et al. (2008) <doi:10.1145/1390156.1390277> for more details.
Analyses: Latent Class Models; Multidimensional Models
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual

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pairwise

Author: Joerg-Henrik Heine
Contact: https://cran.r-project.org/web/packages/pairwise/index.html
Description: pairwise: Rasch Model Parameters by Pairwise Algorithm Performs the explicit calculation - not estimation! - of the Rasch item parameters for dichotomous and polytomous item responses, using a pairwise comparison approach. Person parameters (WLE) are calculated according to Warm's weighted likelihood approach.
Analyses: DIF; Mixture Models
System Requirements: Windows, Linux, or Mac
Measurement Model: Rasch
License Type: Open-Source (R)
Documentation: user manual, sample dataset

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PARSCALE

Author: Eiji Muraki & Darrell Bock
Contact: https://vpgcentral.com/software/scientific-software-international/
Description: This most versatile of all IRT rating-scale programs now includes adjustments for differences in rater severity. PARSCALE 4 now includes: * DIF of rating scale items * Handles up to 15 categories * User options for Samejima's graded response model generalized to rating scales or Master's partial credit model with or without discriminating power parameters. * Allows mixtures of rating scale items and multiple-choice items with or without guessing. * Handles multiple subtests and weighted combinations of subtest scores.
Analyses: DIF; Item & Test Analysis; Reliability; cheating detection
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation: manual in PDF; online help system

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pcIRT

Author: Christine Hohensinn
Contact: https://cran.r-project.org/web/packages/pcIRT
Description: The multidimensional polytomous Rasch model (Rasch, 1961) can be estimated with pcIRT. It provides functions to set linear restrictions on the item category parameters of this models. With this functions it is possible to test whether item categories can be collapsed or set as linear dependent. Thus it is also possible to test whether the multidimensional model can be reduced to a unidimensional model that is whether item categories represent a unidimensional continuum. For this case the scoring parameter of the categories is estimated.
Analyses: Attitude Scaling; Item & Test Analysis; Person Fit/Cheating; Scoring
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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PCMRS

Author: Gunther Schauberger
Contact: https://cran.r-project.org/web/packages/PCMRS/index.html
Description: PCMRS: Model Response Styles in Partial Credit Models. Implementation of PCMRS (Partial Credit Model with Response Styles) as proposed in by Tutz, Schauberger and Berger (2016) <https://epub.ub.uni-muenchen.de/29373/> . PCMRS is an extension of the regular partial credit model. PCMRS allows for an additional person parameter that characterizes the response style of the person. By taking the response style into account, the estimates of the item parameters are less biased than in partial credit models.
Analyses: Cognitive Diagnostic Models; Dimensionality; Latent Class Models; Multidimensional Models; Simulation/Resampling; MCMC
System Requirements: Windows, Linus, or OS
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation:

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PIE

Author: B. A. Hanson, L. Zeng, & Y. Chien
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: PIE conducts IRT true and observed scoring equating for dichotomously scored tests.
Analyses: Cognitive Diagnostic Models; Dimensionality; Item & Test Analysis; Latent Class Models; Multidimensional Models; MCMC
System Requirements: PC Console, PC GUI , MAC OS 9 , MAC OS10
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: Manual in PDF format

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PLmixed

Author: Minjeong Jeon, Nicholas Rockwood
Contact: https://cran.r-project.org/web/packages/PLmixed/index.html
Description: PLmixed: Estimate (Generalized) Linear Mixed Models with Factor Structures. Utilizes the 'lme4' package and the optim() function from 'stats' to estimate (generalized) linear mixed models (GLMM) with factor structures using a profile likelihood approach, as outlined in Jeon and Rabe-Hesketh (2012) <doi:10.3102/1076998611417628>. Factor analysis and item response models can be extended to allow for an arbitrary number of nested and crossed random effects, making it useful for multilevel and cross-classified models.
Analyses: Item & Test Analysis; Scaling; Simulation/Resampling
System Requirements: Windows, Linux, or Mac
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, simulated dataset

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plRasch

Author: Zhushan Li & Feng Hong
Contact: https://cran.r-project.org/web/packages/plRasch/index.html
Description: plRasch: Log Linear by Linear Association models and Rasch family models by pseudolikelihood estimation. Fit Log Linear by Linear Association models and Rasch family models by pseudolikelihood estimation
Analyses: Item & Test Analysis; Latent Class Models; Simulation/Resampling
System Requirements: Windows, Linux, or Mac
Measurement Model: Rasch
License Type: Open-Source (R)
Documentation: user manual

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poLCA

Author: Drew Linzer, Jeffrey Lewis
Contact: https://cran.r-project.org/web/packages/poLCA/index.html
Description: poLCA: Polytomous variable Latent Class Analysis. Latent class analysis and latent class regression models for polytomous outcome variables. Also known as latent structure analysis.
Analyses: Item & Test Analysis; Latent Class Models; Simulation/Resampling
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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polycor

Author: John Fox
Contact: https://cran.r-project.org/web/packages/polycor/index.html
Description: polycor: Polychoric and Polyserial Correlations. Computes polychoric and polyserial correlations by quick two-step methods or ML, optionally with standard errors; tetrachoric and biserial correlations are special cases.
Analyses: Item & Test Analysis; Scoring; Simulation/Resampling; Test Construction & Administration
System Requirements: Windows, Linux, or Mac
Measurement Model: Utilities
License Type: Open-Source (R)
Documentation: user manual

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POLYEQUATE

Author: M. J. Kolen
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: POLYEQUATE conducts IRT true and observed scoring equating for dichotomously and polytomously scored tests.
Analyses: Equating; Scoring
System Requirements: PC Console, MAC OS 9
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: Manual in PDF format

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POLYST

Author: S. Kim & M. J. Kolen
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: POLYST conducts IRT scale transformations for dichotomously and polytomously scored tests.
Analyses: Item & Test Analysis; Scoring; Simulation/Resampling
System Requirements: PC Console, MAC OS 9
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: Manual in PDF format

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PP

Author: Manuel Reif, Jan Steinfeld
Contact: https://cran.r-project.org/web/packages/PP/index.html
Description: PP: Person Parameter Estimation. The PP package includes estimation of (MLE, WLE, MAP, EAP, ROBUST) person parameters for the 1,2,3,4-PL model and the GPCM (generalized partial credit model). The parameters are estimated under the assumption that the item parameters are known and fixed. The package is useful e.g. in the case that items from an item pool / item bank with known item parameters are administered to a new population of test-takers and an ability estimation for every test-taker is needed.
Analyses: DIF
System Requirements: Windows, Linus, or OS
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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PROC IRT

Author: SAS Institute, Inc.
Contact: https://www.sas.com/en_us/home.html
Description: Item response theory (PROC IRT) procedure in SAS/STAT 14.1 to conduct item response theory (IRT) analyses of dichotomous and polytomous datasets that are unidimensional or multidimensional. The review provides an overview of available features, including models, estimation procedures, interfacing, input, and output files. A small-scale simulation study evaluates the IRT model parameter recovery of the PROC IRT procedure. The use of the IRT procedure in Statistical Analysis Software (SAS) may be useful for researchers who frequently utilize SAS for analyses, research, and teaching.
Analyses: DIF; Simulation/Resampling
System Requirements:
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation: Users Guide and examples

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Psych

Author: William Revelle
Contact: https://cran.r-project.org/web/packages/psych/index.html
Description: An R package for personality, psychometric, and psychological research. The psych package includes functions and data sets to do classic and modern psychometrics and to analyze personality and experimental psychological data sets. The psych package has been developed as a supplement to courses in research methods in psychology, personality research, and graduate level psychometric theory. The functions are a supplement to the text (in progress): An introduction to psychometric theory with applications in R.
Analyses: DIF
System Requirements: Windows, Mac, Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: See http://personality-project.org/r/psych_manual.

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psychmeta

Author: Jeffrey Dahlke, Brenton Wiernik
Contact: https://cran.r-project.org/web/packages/psychmeta/index.html
Description: he psychmeta package (Dahlke & Wiernik, 2017/2018) includes tools for computing meta-analyses of correlations and Cohen's d values using bare-bones, individual-correction, and both interactive and Taylor series approximation artifact-distribution methods. The package includes functions to aid in converting a variety of statistical values (e.g., r, d, t, ?2, odds ratios, p values) to the r or d metric. psychmeta's psychometric meta-analysis (PMA) functions support corrections for measurement error and/or range restriction (whether direct or indirect in nature) in one or both variables, as well as numerous other statistical artifacts (Schmidt & Hunter, 2015). psychmeta's meta-analysis functions allow any number of moderators and can analyze moderators hierarchically or as simple effects. psychmeta also includes numerous features to streamline the process of computing meta-analyses.
Analyses: DIF; Simulation/Resampling
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Statistical
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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psychometric

Author: Thomas D. Fletcher
Contact: https://cran.r-project.org/web/packages/psychometric/index.html
Description: Contains functions useful for correlation theory, meta-analysis (validity-generalization), reliability, item analysis, inter-rater reliability, and classical utility
Analyses: DIF; Simulation/Resampling
System Requirements: Windows, Mac, Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: http://cran.wustl.edu/web/packages/psychometric/psychometric.pdf

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psychomix

Author: Hannah Frick, Friedrich Leisch, Carolin Strobl, Florian Wickelmaier, A
Contact: https://cran.r-project.org/web/packages/psychomix/index.html
Description: psychomix: Psychometric Mixture Models. Psychometric mixture models based on 'flexmix' infrastructure. At the moment Rasch mixture models with different parameterizations of the score distribution (saturated vs. mean/variance specification), Bradley-Terry mixture models, and MPT mixture models are implemented. These mixture models can be estimated with or without concomitant variables. See vignette('raschmix', package = 'psychomix') for details on the Rasch mixture models.
Analyses: Test Construction & Administration
System Requirements: Windows, Linux, or Mac
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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qcv

Author: R. Michael Furr, Sarah Heuckeroth
Contact: https://cran.r-project.org/web/packages/qcv/index.html
Description: qcv: Quantifying Construct Validity. Primarily, the 'qcv' package computes key indices related to the Quantifying Construct Validity procedure (QCV; Westen & Rosenthal, 2003 <doi:10.1037/0022-3514.84.3.608>; see also Furr & Heuckeroth, in press). The qcv() function is the heart of the 'qcv' package, but additional functions in the package provide useful ancillary information related to the QCV procedure.
Analyses: Item & Test Analysis; Simulation/Resampling; Test Construction & Administration
System Requirements: Windows, Mac, Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: user manual, sample data

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RAGE-RGEQUATE

Author: l Zeng, M. J. Kolen, B. A. Hanson, Z. Cui, & Y. Ch
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: RAGE_RGEQUATE conducts linear equating and equipercentile equating under the random groups design using cubic spline and log-linear methods.
Analyses: Item & Test Analysis; Simulation/Resampling
System Requirements: PC Console, PC GUI , MAC OS 9 , MAC OS10
Measurement Model: Classical
License Type: Freeware
Documentation: Manual in PDF format

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randomLCA

Author: Ken Beath
Contact: https://cran.r-project.org/web/packages/randomLCA/index.html
Description: randomLCA: Random Effects Latent Class Analysis. Fits standard and random effects latent class models. The single level random effects model is described in Qu et al <doi:10.2307/2533043> and the two level random effects model in Beath and Heller <doi:10.1177/1471082X0800900302>. Examples are given for their use in diagnostic testing.
Analyses: Item & Test Analysis
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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RaschSampler

Author: Patrick Mair, Reinhold Hatzinger, Norman D. Verhelst
Contact: https://cran.r-project.org/web/packages/RaschSampler/index.html
Description: This package implements an MCMC algorithm for sampling of binary matrices with fixed marginscomplying to the Rasch model. Its stationary distribution is uniform. The algorithm also allows forsquare matrices with fixed diagonal.Parameter estimates in the Rasch model only depend on the marginal totals of the data matrix thatis used for the estimation. From this it follows that, if the model is valid, all binary matrices withthe same marginals as the observed one are equally likely. For any statistic of the data matrix, onecan approximate the null distribution, i.e., the distribution if the Rasch model is valid, by taking arandom sample from the collection of equally likely data matrices and constructing the observeddistribution of the statistic. One can then simply determine the exceedence probability of the statis-tic in the observed sample, and thus construct a non-parametric test of the Rasch model. The mainpurpose of this package is the implementation of a methodology to build nonparametric tests for theRasch mode
Analyses: Factor/Latent Structure; Multilevel Data
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Rasch
License Type: Open-Source (R)
Documentation: user manual

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R-CODA

Author: Martyn Plummer
Contact: http://cran.r-project.org/mirrors.html
Description: CODA stands for Convergence Diagnostic and Output Analysis software, and is a menu-driven set of R functions which serves as an output processor for the BUGS software. It may also be used in conjuction with Markov chain Monte Carlo output from a user's own programs, providing the output is formatted appropriately (see the CODA manual for details). CODA computes convergence diagnostics and statistical and graphical summaries for the samples produced by the Gibbs sampler.
Analyses: Factor/Latent Structure; Multidimensional Models; Multilevel Data
System Requirements: UNIX, PC Windows
Measurement Model: Statistical
License Type: Freeware
Documentation: http://www-fis.iarc.fr/coda/faq.html

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ResidPlots-2

Author: Tie Liang, Kyung T. Han & Ronald K. Hambleton
Contact: https://www.umass.edu/remp/software/simcata/residplots/
Description: Computer Software for IRT Graphical Residual Analyses. The purpose of the present software, ResidPlots-2, is to provide a powerful tool for graphical residual analyses.
Analyses: Item & Test Analysis
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: Manual and worked examples can be found from http

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rrum

Author: Steven Andrew Culpepper, Aaron Hudson, James Joseph Balamuta
Contact: https://cran.r-project.org/web/packages/rrum/index.html
Description: rrum: Bayesian Estimation of the Reduced Reparameterized Unified Model with Gibbs Sampling. Implementation of Gibbs sampling algorithm for Bayesian Estimation of the Reduced Reparameterized Unified Model ('rrum'), described by Culpepper and Hudson (2017)
Analyses: Item & Test Analysis; Reliability
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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rsem

Author: Ke-Hai Yuan and Zhiyong Zhang
Contact: https://cran.r-project.org/web/packages/rsem/index.html
Description: rsem: Robust Structural Equation Modeling with Missing Data and Auxiliary Variables. A robust procedure is implemented to estimate means and covariance matrix of multiple variables with missing data using Huber weight and then to estimate a structural equation model.
Analyses: Item & Test Analysis; Multilevel Data
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, simulated datasets

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RUMM

Author: David Andrich
Contact: http://www.rummlab.com.au/
Description: RUMM is a comprehensive item analysis package allowing rapid interaction procedures through its user friendly design and layout; it is a fully operational Windows-based application which means that the creation of Projects, the running of analyses, and the manipulation of screen displays are all facilitated using simple mouse clicks on the range of easy-to-use Windows objects.
Analyses: Item & Test Analysis; Multilevel Data; Rater Effects
System Requirements: Windows
Measurement Model: Rasch
License Type: Commercial
Documentation: manuals, examples, templates

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ScoreGGUM

Author: David R. King & James S. Roberts
Contact: https://cran.r-project.org/web/packages/ScoreGGUM/index.html
Description: The R package ScoreGGUM estimates person parameters and associated standard errors for the GGUM or one of its seven nested variants using an expected a posteriori (EAP) estimator and a posterior standard deviation (Bock & Mislevy, 1982). The user provides the disagree–agree response data to be scored along with the item parameter estimates output file from a previous GGUM2004 calibration.
Analyses: Item & Test Analysis; Multidimensional Models; Scoring
System Requirements: Windows, Mac, Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation:

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SEAsic

Author: Anne Corinne Huggins-Manley & Douglas Whitaker
Contact: https://cran.r-project.org/web/packages/SEAsic/index.html
Description: SEAsic (score equity assessment summary index computation) is an R package for computing and graphing a variety of indices that quantify an important aspect of test fairness, that of reported score equity. SEAsic allows for efficient calculation and graphing of multiple SEA indices. All indices in Huggins and Penfield (2012) can be calculated and plotted in various ways given a user-provided conversion table. Included are the root expected mean square difference (REMSD; Dorans & Holland, 2000), its group-to-overall counterpart (Yang, 2004), and two conditional counterparts, as well as options for manipulating subpopulation and/or score level weights in all of these indices (see Brennan, 2008). All indices from Kolen and Brennan (2004) are included, such as the pairwise mean difference (MD) and absolute mean difference (MAD) indices with options for equal weights (i.e., ewMD, ewMAD) and conditional counterparts. Multiple indices that locate maximum differences (Dorans & Holland, 2000) are also included.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models
System Requirements: Windows, Mac, Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: Manual, multiple examples

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sem

Author: John Fox, Zhenghua Nie, Jarrett Byrnes, Michael Culbertson, Saikat Deb
Contact: https://cran.r-project.org/web/packages/sem/index.html
Description: sem: Structural Equation Models. Functions for fitting general linear structural equation models (with observed and latent variables) using the RAM approach, and for fitting structural equations in observed-variable models by two-stage least squares.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models
System Requirements: Windows, Linux, or Mac
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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semPLS

Author: Armin Monecke, Friedrich Leisch
Contact: https://cran.r-project.org/web/packages/semPLS/index.html
Description: semPLS: Structural Equation Modeling Using Partial Least Squares. Fits structural equation models using partial least squares (PLS). The PLS approach is referred to as 'soft-modeling' technique requiring no distributional assumptions on the observed data.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models
System Requirements: Windows, Linux, or Mac
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, sample data

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semTools

Author: Terrence D. Jorgensen et al.
Contact: https://cran.r-project.org/web/packages/semTools/index.html
Description: semTools: Useful Tools for Structural Equation Modeling. The semTools package provides many miscellaneous functions that are useful for statistical analysis involving SEM in R. Many functions extend the funtionality of thelavaanpackage. Some sets of functions in semTools correspond to the same theme. We call such a collection of functions asuite. Our suites include: Model Fit Evaluation, Measurement Invariance, Power Analysis, Missing Data Analysis, Latent Interactions, Exploratory Factor Analysis (EFA), Reliability Estimation, Parceling, and Non-Normality.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models
System Requirements: Windows, Linux, or Mac
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual, simulated datasets

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ShortForm

Author: Anthony W. Raborn, Walter L. Leite
Contact: https://cran.r-project.org/web/packages/ShortForm/index.html
Description: ShortForm: Automatic Short Form Creation. Performs automatic creation of short forms of scales with an ant colony optimization algorithm and a Tabu search. As implemented in the package, the ant colony algorithm randomly selects items to build a model of a specified length, then updates the probability of item selection according to the fit of the best model within each set of searches. The algorithm continues until the same items are selected by multiple ants a given number of times in a row. On the other hand, the Tabu search changes one parameter at a time to be either free, constrained, or fixed while keeping track of the changes made and putting changes that result in worse fit in a tabu list so that the algorithm does not revisit them for some number of searches. See Leite, Huang, & Marcoulides (2008) <doi:10.1080/00273170802285743> for an applied example of the ant colony algorithm, and Marcoulides & Falk (2018) <doi:10.1080/10705511.2017.1409074> for an applied example of the Tabu search.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models
System Requirements: Windows, Mac, Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: user manual, real and simulated datasets

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SIBTEST

Author: Stout, W., & Roussos, L.
Contact: https://cran.r-project.org/web/packages/sibtest
Description: Classical test theory approach to detecting DIF for unidimensional tests by applying a regression-corrected matched-total score approach. SIBTEST is similar to the Mantel-Haenszel approach for detecting DIF but uses a regression correction based on the KR-20/coefficient alpha reliability index to correct the observed differences when the latent trait distributions are not equal. Function supports the standard SIBTEST for dichotomous and poltomous data (compensatory) and also supports crossed DIF testing (i.e., non-compensatory) for dichotomous data.
Analyses: Dimensionality; Factor/Latent Structure; SEM
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: manual, user's guide, source code

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SIMREL

Author: Halil Yurdugul
Contact: yurdugul@hacettepe.edu.tr
Description: SIMREL: A Software for Coefficient Alpha and Its Confidence Intervals With Monte Carlo Studies. The software runs principal component analysis on data set and calculate distribution coefficient alpha. It is a program designed for the simulation of a coefficients and the estimation of its confidence intervals. It runs on two alternatives. In the first one, if SIMREL is run for a single data file, it performs descriptive statistics, principal components analysis (first eigenvalue and the ratio of first and second eigenvalues as an unidimensionality index), and variance analysis of the item scores in the data file. Following this, it derives unstandardized- standardized coefficient alphas and Armor's Theta from the entire data set. In addition, it calculates the confidence interval estimates of coefficient alphas according to the four different approaches. The second alternative in SIMREL utilizes Monte Carlo simulation. It uses the data employed in the first alternative as population data and obtains estimators of each parameter (such as unidimensionality index, coefficient alphas, Armor's theta, and the boundaries of the confidence intervals obtained from population data) using samples at the desired sample size and replication number from the population data. SIMREL also calculates the bias and the root mean squared error (RMSE) of each estimator. More Detail at: SIMREL: A Software for the coefficient alpha and its confidence intervals with Monte Carlo studies, Applied Psychological Measurement, 33(4), 325-32
Analyses: Dimensionality; Factor/Latent Structure
System Requirements: Windows
Measurement Model: Classical
License Type: Open-Source
Documentation: Manual

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simsem

Author: Terrence D. Jorgensen, Sunthud Pornprasertmanit, Patrick Miller, Alexa
Contact: https://cran.r-project.org/web/packages/simsem/index.html
Description: simsem: SIMulated Structural Equation Modeling. Provides an easy framework for Monte Carlo simulation in structural equation modeling, which can be used for various purposes, such as such as model fit evaluation, power analysis, or missing data handling and planning.
Analyses: Dimensionality; Factor/Latent Structure; SEM
System Requirements: Windows, Linux, or Mac
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual

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SimulCAT

Author: Kyung T. Han
Contact: http://www.hantest.net/simulcat
Description: Most, if not all, computerized adaptive testing (CAT) programs use simulation techniques to develop and evaluate CAT program administration and operations, but such simulation tools are rarely available to the public. Up to now, several software tools have been available to conduct CAT simulations for research purposes; however, these existing tools, for the most part, oversimplify the CAT algorithms and are not powerful enough to simulate operational CAT environments. SimulCAT, a new CAT simulation software tool, was developed to serve various purposes ranging from fundamental CAT research to technical CAT program evaluations. The new CAT simulation software tool offers many advantages, including a wide range of item selection algorithms, adaptability for a variety of CAT administration environments, and a user-friendly graphical interface.
Analyses: Dimensionality; Factor/Latent Structure; SEM
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: User's manual and example data

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SimuMCAT

Author: Lihua Yao
Contact: http://www.bmirt.com/6271.html
Description: SimuMCAT (Yao, 2011) is a computer program for MCAT simulation, which has five MCAT item seelction procedures (includes Angle, Reckase 2009; Volume, Segall, 1996; Kullback-Leibler information; Minimized the error variance of the composite score with optimized weight, Yao, 2010) with item exposure control methods (includes extension of Sympson-Hetter, 1985) and the Multidimensional Priority Index for content constraints.
Analyses: Dimensionality; Factor/Latent Structure; Simulation/Resampling; SEM
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation:

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SimuMIRT

Author: Lihua Yao
Contact: http://www.bmirt.com/6271.html
Description: SimuMIRT (Yao, 2003) is a computer program that simulates examinees (ability) and generate responses to a given set of item paramters specified by the user.
Analyses: Dimensionality; Factor/Latent Structure; SEM
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation:

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sirt

Author: Alexander Robitzsch
Contact: https://cran.r-project.org/web/packages/sirt/
Description: Supplementary Item Response Theory models to complement existing functions in R, including multidimensional compensatory and noncompensatory IRT models, MCMC for hierarchical IRT models and testlet models, NOHARM, Rasch copula model, faceted and hierarchical rater models, ordinal IRT model (ISOP), DETECT statistic, local structural equation modeling (LSEM).
Analyses: Dimensionality; Factor/Latent Structure; Simulation/Resampling; SEM
System Requirements: Windows, Linux, or Mac
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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SNSequate

Author: Jorge Gonzales Burgos
Contact: https://cran.r-project.org/web/packages/SNSequate
Description: The package contains functions to perform various models and methods for test equating. It currently implements the traditional mean, linear and equipercentile equating methods, as well as the mean-mean, mean-sigma, Haebara and Stocking-Lord IRT linking methods. It also supports newest methods such that local equating, kernel equating (using Gaussian, logistic and uniform kernels), and IRT parameterlinking methods based on asymmetric item characteristic functions. Functions to obtain both standard error of equating (SEE) and standard error of equating difference between two equating functions (SEED) are also implmented for the kernel method of equating.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models; SEM
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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SparseFactorAnalysis

Author: Marc Ratkovic, In Song Kim, John Londregan, and Yuki Shiraito
Contact: https://cran.r-project.org/web/packages/SparseFactorAnalysis/index.htm
Description: SparseFactorAnalysis: Scaling Count and Binary Data with Sparse Factor Analysis. Multidimensional scaling provides a means of uncovering a latent structure underlying observed data, while estimating the number of latent dimensions. This package presents a means for scaling binary and count data, for example the votes and word counts for legislators. Future work will include an EM implementation and extend this work to ordinal and continuous data.
Analyses: Dimensionality; Factor/Latent Structure; SEM
System Requirements: Windows, Mac, Linux
Measurement Model: Latent Structure
License Type: Open-Source (R)
Documentation: user manual

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SPSS-AMOS

Author: SPSS Inc.
Contact: www-03.ibm.com/software/products/en/spss-amos/
Description: Amos is powerful structural equation modeling (SEM) software that enables you to support your research and theories by extending standard multivariate analysis methods, including regression, factor analysis, correlation, and analysis of variance. In Amos, you specify, estimate, assess, and present your model in an intuitive path diagram to show hypothesized relationships among variables.
Analyses: Dimensionality; Factor/Latent Structure; SEM
System Requirements: Windows or Mac
Measurement Model: Latent Structure
License Type: Commercial
Documentation: Users' guide in PDF; online help; Amos 5 demo/stud

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ST

Author: L. Zeng, B. A. Hanson, & Y. Chien
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: ST conducts item response theory (IRT) scale transformations for dichotomously scored tests.
Analyses: Item & Test Analysis; Reliability
System Requirements: PC Console, PC GUI , MAC OS 9 , MAC OS10
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: Manual in PDF format

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STDIF

Author: Frederic Robin
Contact: www.umass.edu/remp/software/STDIF.html
Description: STDIF os a DOS-based program to compute DIF indices of conditional p-value differences between two groups of interest: the reference group and the focal group. This is a large-sample procedure requiring a minimum sample size of 10 people in each group at each score point, and was designed to be used with state level data, not pilot samples where sample sizes are typically smaller.
Analyses: Reliability
System Requirements: Windows
Measurement Model: Classical
License Type: Freeware
Documentation: User manual in pdf

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STUIRT

Author: S. Kim & M. J. Kolen
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: STUIRT conduct IRT scale transformations for mixed-format tests.
Analyses: Scaling; Scoring
System Requirements: PC Console
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: Manual in PDF format

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subscore

Author: Shenghai Dai, Xiaolin Wang, Dubravka Svetina
Contact: https://cran.r-project.org/web/packages/subscore/index.html
Description: subscore: Computing Subscores in Classical Test Theory and Item Response Theory. Functions for computing subscores for a test using different methods in both classical test theory (CTT) and item response theory (IRT). This package enables three sets of subscoring methods within the framework of CTT and IRT: Wainer's augmentation method, Haberman's three subscoring methods, and Yen's objective performance index (OPI). The package also includes the function to compute Proportional Reduction of Mean Squared Errors (PRMSEs) in Haberman's methods which are used to examine whether test subscores are of added value.
Analyses: Validity
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: user manual, sample datasets

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TAM

Author: Thomas Kiefer, Alexander Robitzsch, & Margeret Wu
Contact: https://cran.r-project.org/web/packages/TAM
Description: Includes marginal and joint maximum likelihood estimation of uni- and multidimensional item response models (Rasch, 2PL, 3PL, Generalized Partial Credit, Multi Facets, Nominal Item Response, Structured Latent Class Analysis, Mixture Distribution IRT Models, Located Latent Class Models). Latent regression models and plausible value imputation are also supported.
Analyses: Cognitive Diagnostic Models; Factor/Latent Structure; Latent Class Models; Simulation/Resampling
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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TestAssembler

Author: Assessment Systems Corp.
Contact: https://assess.com/testassembler/
Description: TestAssembler is a simple, effective tool for automated test assembly based on classical test theory (CTT) or item response theory (IRT), including anchor item blocks. It was designed with one purpose in mind: to save you time and money.
Analyses: Factor/Latent Structure; Latent Class Models; Multidimensional Models
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation:

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TestScorer

Author: Manel Salamero
Contact: https://cran.r-project.org/web/packages/TestScorer
Description: GUI for entering test items and obtaining raw and transformed scores. The results are shown on the console and can be saved to a tabular text file for further statistical analysis. The user can define his own tests and scoring procedures through a GUI.
Analyses: Factor/Latent Structure; Latent Class Models; Multidimensional Models
System Requirements: Windows, Mac OS, & Linux
Measurement Model: Classical
License Type: Open-Source (R)
Documentation: User manual in pdf

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urGENOVA

Author: R. L. Brennan
Contact: https://education.uiowa.edu/centers/center-advanced-studies-measurement-and-assessment/computer-programs
Description: urGENOVA is an ANSI C computer program for the estimation of variance components for unbalanced random effects G study? designs. The program does not have D study capabilities.
Analyses: Dimensionality; Factor/Latent Structure; Multidimensional Models; Bayesian latent variable models
System Requirements: Mac, Windows
Measurement Model: Classical
License Type: Freeware
Documentation: Manual in PDF format

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WINBUGS/BUGS

Author: Lunn, D.J., Thomas, A., Best, N., and Spiegelhalte
Contact: www.mrc-bsu.cam.ac.uk/software/bugs/
Description: The BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. The project began in 1989 in the MRC Biostatistics Unit and led initially to the `Classic' BUGS program, and then onto the WinBUGS software developed jointly with the Imperial College School of Medicine at St Mary's, London.
Analyses: Factor/Latent Structure; Multidimensional Models; Simulation/Resampling; MCMC
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Open-Source
Documentation: PDF manual, three volumes of examples, source code

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WinGen

Author: Kyung (Chris) T. Han
Contact: http://www.umass.edu/remp/software/simcata/wingen/homeF.html
Description: A computer program, called WinGen (Han, 2006) was developed to generate dichotomous and polytomous item response data for several IRT models and for many conditions that arise in practice. Although many IRT model simulation software programs have been developed, most of them were designed for intentionally narrow purposes since they were not publicly shared programs. WinGen is more general and more user friendly than many of the IRT simulation programs available today. WinGen is easy to use with an intuitive, user-friendly interface while providing very strong research tools and performance at the same time. Thus, WinGen should be useful for researchers who want to do simulation research, and students who are eager to learn more about IRT.
Analyses: Dimensionality; Factor/Latent Structure; Latent Class Models; Multidimensional Models
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Freeware
Documentation: Online manual at http://www.umass.edu/remp/softwar

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WINMIRA

Author: Matthias von Davier
Contact: http://www.von-davier.com/
Description: WINMIRA is standalone software for estimating and testing a large number of discrete mixture models for categorical variables. Models with a nominal as well as continuous latent variables, and combinations of both, can be estimated with the software. WINMIRA 2001 can be used for analyses with the Latent Class Analysis (LCA), with the Rasch model (RM), with the Mixed Rasch model (MRM) and with Hybrid models (HYBRID) for dichotomous and polytomous data.
Analyses: Generalizability
System Requirements: Windows
Measurement Model: Rasch
License Type: Commercial
Documentation: manual in PDF; demo version

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WINSTEPS

Author: J. M. Linacre
Contact: http://www.winsteps.com/
Description: Winsteps is Windows-based software which assists with many applications of the Rasch model, particularly in the areas of educational testing, attitude surveys and rating scale analysis. Rasch analysis is a method for obtaining objective, fundamental, linear measures (qualified by standard errors and quality-control fit statistics) from stochastic observations of ordered category responses. Georg Rasch, a Danish mathematician, formulated this approach in 1953 to analyze responses to a series of reading tests (Rasch G, Probabilistic Models for Some Intelligence and Attainment Tests, Chicago: MESA Press, 1992, with instructive Foreword and Afterword by B.D. Wright). The Rasch models implemented in Winsteps include the Georg Rasch dichotomous, Andrich rating scale, Masters partial credit, Bradley-Terry paired comparison, Glas success model, Linacre failure model and most combinations of these models. Other models such as binomial trials and Poisson can also be analyzed by anchoring (fixing) the response structure to accord with the response model
Analyses: Cognitive Diagnostic Models; Latent Class Models; Multidimensional Models; Simulation/Resampling
System Requirements: Windows;Mac
Measurement Model: Rasch
License Type: Commercial
Documentation: student version; online manual; manual in PDF

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WrightMap

Author: David Torres Irribarra & Rebecca Freund
Contact: https://cran.r-project.org/web/packages/WrightMap
Description: A powerful yet simple graphical tool available in the field of psychometrics is the Wright Map (also known as item maps or item-person maps), which presents the location of both respondents and items on the same scale. Wright Maps are commonly used to present the results of dichotomous or polytomous item response models. The WrightMap package provides functions to create these plots from item parameters and person estimates stored as R objects. Although the package can be used in conjunction with any software used to estimate the IRT model (e.g. eRm or IRToys in R, or Stata, Mplus, etc.), WrightMap features special integration with ConQuest to facilitate reading and plotting its output directly.The wrightMap function creates Wright Maps based on person estimates and item parameters produced by an item response analysis. The CQmodel function reads output files created using ConQuest software and creates a set of data frames for easy data manipulation, bundled in a CQmodel object. The wrightMap function can take a CQmodel object as input or it can be used to create Wright Maps directly from data frames of person and item parameters. WrightMap features special integration with ConQuest to facilitate reading and plotting its output directly.
Analyses: meta-analysis
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: User manual in pdf

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XCALIBRE

Author: Assessment Systems Corp.
Contact: https://assess.com/xcalibre/
Description: Xcalibre represents the leading edge in software for item response theory (IRT) analysis of assessments. Xcalibre calibrates your test using 4 dichotomous and 5 polytomous IRT models, and produces professional reports summarizing the analysis, complete with embedded graphics and tables. It also includes differential item functioning and IRT linking. Xcalibre is the most user-friendly IRT software available, with a purely point-and-click interface - no programming code!
Analyses: Attitude Scaling; Item & Test Analysis; Simulation/Resampling
System Requirements: Windows
Measurement Model: IRT/Rasch
License Type: Commercial
Documentation: demo version; online manual

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xxIRT

Author: Xiao Luo
Contact: https://cran.r-project.org/web/packages/xxIRT/index.html
Description: xxIRT: Item Response Theory and Computer-Based Testing in R. A suite of psychometric analysis tools for research and operation, including: (1) computation of probability, information, and likelihood for the 3PL, GPCM, and GRM; (2) parameter estimation using joint or marginal likelihood estimation method; (3) simulation of computerized adaptive testing using built-in or customized algorithms; (4) assembly and simulation of multistage testing. The full documentation and tutorials are at <https://github.com/xluo11/xxIRT>
Analyses: Scaling; Scoring; Test Construction & Administration
System Requirements: Windows, Mac OS, & Linux
Measurement Model: IRT/Rasch
License Type: Open-Source (R)
Documentation: user manual

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