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Haeju Lee; Kyung Yong Kim – Journal of Educational Measurement, 2025
When no prior information of differential item functioning (DIF) exists for items in a test, either the rank-based or iterative purification procedure might be preferred. The rank-based purification selects anchor items based on a preliminary DIF test. For a preliminary DIF test, likelihood ratio test (LRT) based approaches (e.g.,…
Descriptors: Test Items, Equated Scores, Test Bias, Accuracy
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Tom Benton – Practical Assessment, Research & Evaluation, 2025
This paper proposes an extension of linear equating that may be useful in one of two fairly common assessment scenarios. One is where different students have taken different combinations of test forms. This might occur, for example, where students have some free choice over the exam papers they take within a particular qualification. In this…
Descriptors: Equated Scores, Test Format, Test Items, Computation
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Youn Seon Lim – Journal of Educational Measurement, 2025
While testlets have proven useful for assessing complex skills, the stem shared by multiple items often induces correlations between responses, leading to violations of local independence (LI), which can result in biased parameter and ability estimates. Diagnostic procedures for detecting testlet effects typically involve model comparisons testing…
Descriptors: Sampling, Statistical Inference, Tests, Statistical Analysis
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Sun-Joo Cho; Goodwin Amanda; Jorge Salas; Sophia Mueller – Grantee Submission, 2025
This study incorporates a random forest (RF) approach to probe complex interactions and nonlinearity among predictors into an item response model with the goal of using a hybrid approach to outperform either an RF or explanatory item response model (EIRM) only in explaining item responses. In the specified model, called EIRM-RF, predicted values…
Descriptors: Item Response Theory, Artificial Intelligence, Statistical Analysis, Predictor Variables
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Abdulla Alzarouni; R. J. De Ayala – Practical Assessment, Research & Evaluation, 2025
The assessment of model fit in latent trait modeling is an integral part of correctly applying the model. Still the assessment of model fit has been less utilized for ideal point models such as the Generalized Graded Unfolding Models (GGUM). The current study assesses the performance of the relative fit indices "AIC" and "BIC,"…
Descriptors: Goodness of Fit, Models, Statistical Analysis, Sample Size
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Inga Laukaityte; Marie Wiberg – Practical Assessment, Research & Evaluation, 2024
The overall aim was to examine effects of differences in group ability and features of the anchor test form on equating bias and the standard error of equating (SEE) using both real and simulated data. Chained kernel equating, Postratification kernel equating, and Circle-arc equating were studied. A college admissions test with four different…
Descriptors: Ability Grouping, Test Items, College Entrance Examinations, High Stakes Tests
Jiajing Huang – ProQuest LLC, 2022
The nonequivalent-groups anchor-test (NEAT) data-collection design is commonly used in large-scale assessments. Under this design, different test groups take different test forms. Each test form has its own unique items and all test forms share a set of common items. If item response theory (IRT) models are applied to analyze the test data, the…
Descriptors: Item Response Theory, Test Format, Test Items, Test Construction
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He, Qingping; Meadows, Michelle; Black, Beth – Research Papers in Education, 2022
A potential negative consequence of high-stakes testing is inappropriate test behaviour involving individuals and/or institutions. Inappropriate test behaviour and test collusion can result in aberrant response patterns and anomalous test scores and invalidate the intended interpretation and use of test results. A variety of statistical techniques…
Descriptors: Statistical Analysis, High Stakes Tests, Scores, Response Style (Tests)
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Su, Kun; Henson, Robert A. – Journal of Educational and Behavioral Statistics, 2023
This article provides a process to carefully evaluate the suitability of a content domain for which diagnostic classification models (DCMs) could be applicable and then optimized steps for constructing a test blueprint for applying DCMs and a real-life example illustrating this process. The content domains were carefully evaluated using a set of…
Descriptors: Classification, Models, Science Tests, Physics
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Weese, James D.; Turner, Ronna C.; Ames, Allison; Crawford, Brandon; Liang, Xinya – Educational and Psychological Measurement, 2022
A simulation study was conducted to investigate the heuristics of the SIBTEST procedure and how it compares with ETS classification guidelines used with the Mantel-Haenszel procedure. Prior heuristics have been used for nearly 25 years, but they are based on a simulation study that was restricted due to computer limitations and that modeled item…
Descriptors: Test Bias, Heuristics, Classification, Statistical Analysis
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Robitzsch, Alexander; Lüdtke, Oliver – Journal of Educational and Behavioral Statistics, 2022
One of the primary goals of international large-scale assessments in education is the comparison of country means in student achievement. This article introduces a framework for discussing differential item functioning (DIF) for such mean comparisons. We compare three different linking methods: concurrent scaling based on full invariance,…
Descriptors: Test Bias, International Assessment, Scaling, Comparative Analysis
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Mark Wilson – Journal of Educational and Behavioral Statistics, 2024
This article introduces a new framework for articulating how educational assessments can be related to teacher uses in the classroom. It articulates three levels of assessment: macro (use of standardized tests), meso (externally developed items), and micro (on-the-fly in the classroom). The first level is the usual context for educational…
Descriptors: Educational Assessment, Measurement, Standardized Tests, Test Items
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Demirkaya, Onur; Bezirhan, Ummugul; Zhang, Jinming – Journal of Educational and Behavioral Statistics, 2023
Examinees with item preknowledge tend to obtain inflated test scores that undermine test score validity. With the availability of process data collected in computer-based assessments, the research on detecting item preknowledge has progressed on using both item scores and response times. Item revisit patterns of examinees can also be utilized as…
Descriptors: Test Items, Prior Learning, Knowledge Level, Reaction Time
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Marc Brysbaert – Cognitive Research: Principles and Implications, 2024
Experimental psychology is witnessing an increase in research on individual differences, which requires the development of new tasks that can reliably assess variations among participants. To do this, cognitive researchers need statistical methods that many researchers have not learned during their training. The lack of expertise can pose…
Descriptors: Experimental Psychology, Individual Differences, Statistical Analysis, Task Analysis
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Wang, Weimeng; Liu, Yang; Liu, Hongyun – Journal of Educational and Behavioral Statistics, 2022
Differential item functioning (DIF) occurs when the probability of endorsing an item differs across groups for individuals with the same latent trait level. The presence of DIF items may jeopardize the validity of an instrument; therefore, it is crucial to identify DIF items in routine operations of educational assessment. While DIF detection…
Descriptors: Test Bias, Test Items, Equated Scores, Regression (Statistics)
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