Sandip Sinharay, ETS
Dear JEM Readers,
I sincerely hope that you and your family are all safe and sound. This JEM issue is being published at a time when the world is going through an unprecedented crisis due to the COVID19 pandemic and most of you are probably affected one way or another by the pandemic. The testing industry is being severely impacted by the pandemic as well. The long-term impact of COVID19 on educational measurement will be the focus of multiple short manuscripts that will be published in the Fall 2020 issue of Educational Measurement: Issues and Practice (EMIP), JEM’s sister journal.
This JEM issue includes eight articles on a wide variety of topics. The first four articles are somewhat unique in the sense that they are invited articles and relate to the invited presentation of Shelby Haberman at the 2019 annual meeting of the National Council on Measurement in Education (NCME)—the presentation was a part of Prof. Haberman’s receipt of the 2019 NCME Award for Career Contributions to Educational Measurement. The first article, “Statistical Theory and Assessment Practice” and is an adaptation of the 2019 presentation of Shelby Haberman. This article is an outstanding statistician’s take on educational measurement and should be illuminating to all JEM readers. The second and third articles are comments on “Statistical Theory and Assessment Practice” by Robert Mislevy and David Thissen who themselves won the award in 2003 and 2015, respectively. The fourth article, again by Shelby Haberman, is a rejoinder to “Statistical Theory and Assessment Practice” and includes responses to some comments of Robert Mislevy and David Thissen. In the fifth article, Wim van der Linden and Seung Choi suggest improvements in controlling item exposure on computerized adaptive tests. In the sixth article, Scott Monroe and Seong Eun Hong examine the performance of person-fit statistics when the underlying item response theory model is misspecified. In the seventh article, Sunbok Lee examines whether the use of a penalized maximum likelihood estimation approach leads to an improvement in the analysis of differential item functioning using the logistic regression procedure. In the final article of the issue, Chunyan Liu and Michael Kolen present a new statistic for selecting the smoothing parameter for polynomial loglinear equating under the random groups equating design.
Reviewers have played a very important role in the smooth functioning of the JEM review process and their contributions are acknowledged at the end of this issue.
I hope you find this issue interesting and informative.