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Ye Ma; Deborah J. Harris – Educational Measurement: Issues and Practice, 2025
Item position effect (IPE) refers to situations where an item performs differently when it is administered in different positions on a test. The majority of previous research studies have focused on investigating IPE under linear testing. There is a lack of IPE research under adaptive testing. In addition, the existence of IPE might violate Item…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
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Sweeney, Sandra M.; Sinharay, Sandip; Johnson, Matthew S.; Steinhauer, Eric W. – Educational Measurement: Issues and Practice, 2022
The focus of this paper is on the empirical relationship between item difficulty and item discrimination. Two studies--an empirical investigation and a simulation study--were conducted to examine the association between item difficulty and item discrimination under classical test theory and item response theory (IRT), and the effects of the…
Descriptors: Correlation, Item Response Theory, Item Analysis, Difficulty Level
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Cuhadar, Ismail; Binici, Salih – Educational Measurement: Issues and Practice, 2022
This study employs the 4-parameter logistic item response theory model to account for the unexpected incorrect responses or slipping effects observed in a large-scale Algebra 1 End-of-Course assessment, including several innovative item formats. It investigates whether modeling the misfit at the upper asymptote has any practical impact on the…
Descriptors: Item Response Theory, Measurement, Student Evaluation, Algebra
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Zhan, Peida; He, Keren – Educational Measurement: Issues and Practice, 2021
In learning diagnostic assessments, the attribute hierarchy specifies a sequential network of interrelated attribute mastery processes, which makes a test blueprint consistent with the cognitive theory. One of the most important functions of attribute hierarchy is to guide or limit the developmental direction of students and then form a…
Descriptors: Longitudinal Studies, Models, Comparative Analysis, Diagnostic Tests
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Leventhal, Brian; Ames, Allison – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Brian Leventhal and Dr. Allison Ames provide an overview of "Monte Carlo simulation studies" (MCSS) in "item response theory" (IRT). MCSS are utilized for a variety of reasons, one of the most compelling being that they can be used when analytic solutions are impractical or nonexistent because…
Descriptors: Item Response Theory, Monte Carlo Methods, Simulation, Test Items
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Goeman, J. J.; De Jong, N. H. – Educational Measurement: Issues and Practice, 2018
Many researchers use Cronbach's alpha to demonstrate internal consistency, even though it has been shown numerous times that Cronbach's alpha is not suitable for this. Because the intention of questionnaire and test constructers is to summarize the test by its overall sum score, we advocate summability, which we define as the proportion of total…
Descriptors: Tests, Scores, Questionnaires, Measurement
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Wind, Stefanie A.; Walker, A. Adrienne – Educational Measurement: Issues and Practice, 2021
Many large-scale performance assessments include score resolution procedures for resolving discrepancies in rater judgments. The goal of score resolution is conceptually similar to person fit analyses: To identify students for whom observed scores may not accurately reflect their achievement. Previously, researchers have observed that…
Descriptors: Goodness of Fit, Performance Based Assessment, Evaluators, Decision Making
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Yocarini, Iris E.; Bouwmeester, Samantha; Smeets, Guus; Arends, Lidia R. – Educational Measurement: Issues and Practice, 2018
This real-data-guided simulation study systematically evaluated the decision accuracy of complex decision rules combining multiple tests within different realistic curricula. Specifically, complex decision rules combining conjunctive aspects and compensatory aspects were evaluated. A conjunctive aspect requires a minimum level of performance,…
Descriptors: Comparative Analysis, Decision Making, Accuracy, Higher Education
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Luecht, Richard; Ackerman, Terry A. – Educational Measurement: Issues and Practice, 2018
Simulation studies are extremely common in the item response theory (IRT) research literature. This article presents a didactic discussion of "truth" and "error" in IRT-based simulation studies. We ultimately recommend that future research focus less on the simple recovery of parameters from a convenient generating IRT model,…
Descriptors: Item Response Theory, Simulation, Ethics, Error of Measurement
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Yoo, Hanwook; Hambleton, Ronald K. – Educational Measurement: Issues and Practice, 2019
Item analysis is an integral part of operational test development and is typically conducted within two popular statistical frameworks: classical test theory (CTT) and item response theory (IRT). In this digital ITEMS module, Hanwook Yoo and Ronald K. Hambleton provide an accessible overview of operational item analysis approaches within these…
Descriptors: Item Analysis, Item Response Theory, Guidelines, Test Construction
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Madison, Matthew J. – Educational Measurement: Issues and Practice, 2019
Recent advances have enabled diagnostic classification models (DCMs) to accommodate longitudinal data. These longitudinal DCMs were developed to study how examinees change, or transition, between different attribute mastery statuses over time. This study examines using longitudinal DCMs as an approach to assessing growth and serves three purposes:…
Descriptors: Longitudinal Studies, Item Response Theory, Psychometrics, Criterion Referenced Tests
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Rutkowski, David; Rutkowski, Leslie; Liaw, Yuan-Ling – Educational Measurement: Issues and Practice, 2018
Participation in international large-scale assessments has grown over time with the largest, the Programme for International Student Assessment (PISA), including more than 70 education systems that are economically and educationally diverse. To help accommodate for large achievement differences among participants, in 2009 PISA offered…
Descriptors: Educational Assessment, Foreign Countries, Achievement Tests, Secondary School Students
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Wyse, Adam E. – Educational Measurement: Issues and Practice, 2017
This article illustrates five different methods for estimating Angoff cut scores using item response theory (IRT) models. These include maximum likelihood (ML), expected a priori (EAP), modal a priori (MAP), and weighted maximum likelihood (WML) estimators, as well as the most commonly used approach based on translating ratings through the test…
Descriptors: Cutting Scores, Item Response Theory, Bayesian Statistics, Maximum Likelihood Statistics