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 search and filter functions to find a certain software or narrow options by analysis, license, and measurement model.
- Software Database (172)
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.
System Requirements: Windows, Macs running Windows 32- & 64-bit versions
Documentation: demo version & tutorials trial version available
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
System Requirements:
Documentation:
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.
System Requirements: Windows 95 or Higher
Documentation: manual; input/output files for sample analyses
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.
System Requirements: Windows, Linux, or Mac
Documentation: user manual
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
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
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
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
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:
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