Short scales are time-efficient for participants and cost-effective in research. However, researchers often mistakenly expect short scales to have the same reliability as long ones without considering the effect of scale length. We argue that applying a universal benchmark for alpha is problematic as the impact of low-quality items is greater on…

The subjective aspect of standard-setting is often criticized, yet data-driven standard-setting methods are rarely applied. Therefore, we applied a mixture Rasch model approach to setting performance standards across several testing programs of various sizes and compared the results to existing passing standards derived from traditional…

Population invariance is a desirable property of test equating which might not hold when significant changes occur in the test population, such as those brought about by the COVID-19 pandemic. This research aims to investigate whether equating functions are reasonably invariant when the test population is impacted by the pandemic. Based on…

Test equating requires collecting data to link the scores from different forms of a test. Problems arise when equating samples are not equivalent and the test forms to be linked share no common items by which to measure or adjust for the group nonequivalence. Using data from five operational test forms, we created five pairs of research forms for…

This article proposes a Boolean approach to representing and analyzing interobserver agreement in dichotomous coding. Building on the notion that observations are samples of a universe of observations, it submits that coding can be viewed as a process in which observers sample pieces of evidence on constructs. It distinguishes between formal and…

Commonly used machine learning applications seem to relate to big data. This article provides a gentle review of machine learning and shows why machine learning can be applied to small data too. An example of applying machine learning to screen irregularity reports is presented. In the example, the support vector machine and multinomial naïve…

This study addresses measurement issues around a standards-based content analysis of mathematics textbooks' coverage of standards for use in large-scale monitoring of standards implementation as proposed in a 2013 report by the National Research Council. An earlier study produced an exhaustive content analysis of textbooks using the 2012 Common…

A longstanding concern about admissions to higher education is the underprediction of female academic performance by admission test scores. One explanation for these findings is selection system bias, that is, not all relevant KSAOs that are related to academic performance and gender are included in the prediction model. One solution to this…

Cut-scores were set by expert judges on assessments of reading and listening comprehension of English as a foreign language (EFL), using the bookmark standard-setting method to differentiate proficiency levels defined by the Common European Framework of Reference (CEFR). Assessments contained stratified item samples drawn from extensive item…

Examined in this study were the effects of reducing anchor test length on student proficiency rates for 12 multiple-choice tests administered in an annual, large-scale, high-stakes assessment. The anchor tests contained 15 items, 10 items, or five items. Five content representative samples of items were drawn at each anchor test length from a…

In large-scale assessments, such as state-wide testing programs, national sample-based assessments, and international comparative studies, there are many steps involved in the measurement and reporting of student achievement. There are always sources of inaccuracies in each of the steps. It is of interest to identify the source and magnitude of…

The purpose of this ITEMS module is to provide an introduction to Markov chain Monte Carlo (MCMC) estimation for item response models. A brief description of Bayesian inference is followed by an overview of the various facets of MCMC algorithms, including discussion of prior specification, sampling procedures, and methods for evaluating chain…

Cohen and Hyman's response contains several misunderstandings of the original article by Mehrens and Kaminski. One frequently wishes to make inferences to a domain from a test, but teaching a specific performance and testing for that performance does not allow for a domain inference. (SLD)

Issues concerning the selection of judges for standard setting are discussed. Determining the consistency of judges' recommendations, or their congruity with other expert recommendations, would help in selection. Enough judges must be chosen to allow estimation of recommendations by an entire population of judges. (SLD)