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Okan Bulut; Guher Gorgun; Hacer Karamese – Journal of Educational Measurement, 2025
The use of multistage adaptive testing (MST) has gradually increased in large-scale testing programs as MST achieves a balanced compromise between linear test design and item-level adaptive testing. MST works on the premise that each examinee gives their best effort when attempting the items, and their responses truly reflect what they know or can…
Descriptors: Response Style (Tests), Testing Problems, Testing Accommodations, Measurement
Chun Wang; Ping Chen; Shengyu Jiang – Journal of Educational Measurement, 2020
Many large-scale educational surveys have moved from linear form design to multistage testing (MST) design. One advantage of MST is that it can provide more accurate latent trait [theta] estimates using fewer items than required by linear tests. However, MST generates incomplete response data by design; hence, questions remain as to how to…
Descriptors: Test Construction, Test Items, Adaptive Testing, Maximum Likelihood Statistics
Sinharay, Sandip – Journal of Educational Measurement, 2017
Person-fit assessment (PFA) is concerned with uncovering atypical test performance as reflected in the pattern of scores on individual items on a test. Existing person-fit statistics (PFSs) include both parametric and nonparametric statistics. Comparison of PFSs has been a popular research topic in PFA, but almost all comparisons have employed…
Descriptors: Goodness of Fit, Testing, Test Items, Scores
Sinharay, Sandip; Wan, Ping; Choi, Seung W.; Kim, Dong-In – Journal of Educational Measurement, 2015
With an increase in the number of online tests, the number of interruptions during testing due to unexpected technical issues seems to be on the rise. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees' scores. Researchers such as…
Descriptors: Computer Assisted Testing, Testing Problems, Scores, Statistical Analysis
Sinharay, Sandip; Duong, Minh Q.; Wood, Scott W. – Journal of Educational Measurement, 2017
As noted by Fremer and Olson, analysis of answer changes is often used to investigate testing irregularities because the analysis is readily performed and has proven its value in practice. Researchers such as Belov, Sinharay and Johnson, van der Linden and Jeon, van der Linden and Lewis, and Wollack, Cohen, and Eckerly have suggested several…
Descriptors: Identification, Statistics, Change, Tests
Köhler, Carmen; Pohl, Steffi; Carstensen, Claus H. – Journal of Educational Measurement, 2017
Competence data from low-stakes educational large-scale assessment studies allow for evaluating relationships between competencies and other variables. The impact of item-level nonresponse has not been investigated with regard to statistics that determine the size of these relationships (e.g., correlations, regression coefficients). Classical…
Descriptors: Test Items, Cognitive Measurement, Testing Problems, Regression (Statistics)
Lu, Jing; Wang, Chun – Journal of Educational Measurement, 2020
Item nonresponses are prevalent in standardized testing. They happen either when students fail to reach the end of a test due to a time limit or quitting, or when students choose to omit some items strategically. Oftentimes, item nonresponses are nonrandom, and hence, the missing data mechanism needs to be properly modeled. In this paper, we…
Descriptors: Item Response Theory, Test Items, Standardized Tests, Responses
Sinharay, Sandip; Wan, Ping; Whitaker, Mike; Kim, Dong-In; Zhang, Litong; Choi, Seung W. – Journal of Educational Measurement, 2014
With an increase in the number of online tests, interruptions during testing due to unexpected technical issues seem unavoidable. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees' scores. There is a lack of research on this…
Descriptors: Computer Assisted Testing, Testing Problems, Scores, Regression (Statistics)
Debeer, Dries; Janssen, Rianne; De Boeck, Paul – Journal of Educational Measurement, 2017
When dealing with missing responses, two types of omissions can be discerned: items can be skipped or not reached by the test taker. When the occurrence of these omissions is related to the proficiency process the missingness is nonignorable. The purpose of this article is to present a tree-based IRT framework for modeling responses and omissions…
Descriptors: Item Response Theory, Test Items, Responses, Testing Problems
Myford, Carol M.; Wolfe, Edward W. – Journal of Educational Measurement, 2009
In this study, we describe a framework for monitoring rater performance over time. We present several statistical indices to identify raters whose standards drift and explain how to use those indices operationally. To illustrate the use of the framework, we analyzed rating data from the 2002 Advanced Placement English Literature and Composition…
Descriptors: English Literature, Advanced Placement, Measures (Individuals), Writing (Composition)
Clauser, Brian E.; Mee, Janet; Baldwin, Su G.; Margolis, Melissa J.; Dillon, Gerard F. – Journal of Educational Measurement, 2009
Although the Angoff procedure is among the most widely used standard setting procedures for tests comprising multiple-choice items, research has shown that subject matter experts have considerable difficulty accurately making the required judgments in the absence of examinee performance data. Some authors have viewed the need to provide…
Descriptors: Standard Setting (Scoring), Program Effectiveness, Expertise, Health Personnel
Cui, Ying; Leighton, Jacqueline P. – Journal of Educational Measurement, 2009
In this article, we introduce a person-fit statistic called the hierarchy consistency index (HCI) to help detect misfitting item response vectors for tests developed and analyzed based on a cognitive model. The HCI ranges from -1.0 to 1.0, with values close to -1.0 indicating that students respond unexpectedly or differently from the responses…
Descriptors: Test Length, Simulation, Correlation, Research Methodology
van der Linden, Wim J.; Breithaupt, Krista; Chuah, Siang Chee; Zhang, Yanwei – Journal of Educational Measurement, 2007
A potential undesirable effect of multistage testing is differential speededness, which happens if some of the test takers run out of time because they receive subtests with items that are more time intensive than others. This article shows how a probabilistic response-time model can be used for estimating differences in time intensities and speed…
Descriptors: Adaptive Testing, Evaluation Methods, Test Items, Reaction Time
de La Torre, Jimmy; Karelitz, Tzur M. – Journal of Educational Measurement, 2009
Compared to unidimensional item response models (IRMs), cognitive diagnostic models (CDMs) based on latent classes represent examinees' knowledge and item requirements using discrete structures. This study systematically examines the viability of retrofitting CDMs to IRM-based data with a linear attribute structure. The study utilizes a procedure…
Descriptors: Simulation, Item Response Theory, Psychometrics, Evaluation Methods

Trentham, Landa L. – Journal of Educational Measurement, 1975
Descriptors: Comparative Testing, Educational Testing, Elementary Education, Grade 6