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Jyun-Hong Chen; Hsiu-Yi Chao – Journal of Educational and Behavioral Statistics, 2024
To solve the attenuation paradox in computerized adaptive testing (CAT), this study proposes an item selection method, the integer programming approach based on real-time test data (IPRD), to improve test efficiency. The IPRD method turns information regarding the ability distribution of the population from real-time test data into feasible test…
Descriptors: Data Use, Computer Assisted Testing, Adaptive Testing, Design
Daniel Koretz – Journal of Educational and Behavioral Statistics, 2024
A critically important balance in educational measurement between practical concerns and matters of technique has atrophied in recent decades, and as a result, some important issues in the field have not been adequately addressed. I start with the work of E. F. Lindquist, who exemplified the balance that is now wanting. Lindquist was arguably the…
Descriptors: Educational Assessment, Evaluation Methods, Achievement Tests, Educational History
Wim J. van der Linden; Luping Niu; Seung W. Choi – Journal of Educational and Behavioral Statistics, 2024
A test battery with two different levels of adaptation is presented: a within-subtest level for the selection of the items in the subtests and a between-subtest level to move from one subtest to the next. The battery runs on a two-level model consisting of a regular response model for each of the subtests extended with a second level for the joint…
Descriptors: Adaptive Testing, Test Construction, Test Format, Test Reliability
Joshua B. Gilbert; Luke W. Miratrix; Mridul Joshi; Benjamin W. Domingue – Journal of Educational and Behavioral Statistics, 2025
Analyzing heterogeneous treatment effects (HTEs) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and preintervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…
Descriptors: Causal Models, Item Response Theory, Statistical Inference, Psychometrics
Giada Spaccapanico Proietti; Mariagiulia Matteucci; Stefania Mignani; Bernard P. Veldkamp – Journal of Educational and Behavioral Statistics, 2024
Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…
Descriptors: Automation, Computer Assisted Testing, Ambiguity (Context), Item Response Theory
Grabovsky, Irina; Wainer, Howard – Journal of Educational and Behavioral Statistics, 2017
In this essay, we describe the construction and use of the Cut-Score Operating Function in aiding standard setting decisions. The Cut-Score Operating Function shows the relation between the cut-score chosen and the consequent error rate. It allows error rates to be defined by multiple loss functions and will show the behavior of each loss…
Descriptors: Cutting Scores, Standard Setting (Scoring), Decision Making, Error Patterns
Chen, Ping – Journal of Educational and Behavioral Statistics, 2017
Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…
Descriptors: Test Items, Item Response Theory, Test Construction, Adaptive Testing
Thissen, David – Journal of Educational and Behavioral Statistics, 2016
David Thissen, a professor in the Department of Psychology and Neuroscience, Quantitative Program at the University of North Carolina, has consulted and served on technical advisory committees for assessment programs that use item response theory (IRT) over the past couple decades. He has come to the conclusion that there are usually two purposes…
Descriptors: Item Response Theory, Test Construction, Testing Problems, Student Evaluation