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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
Chen, Yunxiao; Lee, Yi-Hsuan; Li, Xiaoou – Journal of Educational and Behavioral Statistics, 2022
In standardized educational testing, test items are reused in multiple test administrations. To ensure the validity of test scores, the psychometric properties of items should remain unchanged over time. In this article, we consider the sequential monitoring of test items, in particular, the detection of abrupt changes to their psychometric…
Descriptors: Standardized Tests, Test Items, Test Validity, Scores
Zhan, Peida; Jiao, Hong; Man, Kaiwen; Wang, Lijun – Journal of Educational and Behavioral Statistics, 2019
In this article, we systematically introduce the just another Gibbs sampler (JAGS) software program to fit common Bayesian cognitive diagnosis models (CDMs) including the deterministic inputs, noisy "and" gate model; the deterministic inputs, noisy "or" gate model; the linear logistic model; the reduced reparameterized unified…
Descriptors: Bayesian Statistics, Computer Software, Models, Test Items
Oranje, Andreas; Kolstad, Andrew – Journal of Educational and Behavioral Statistics, 2019
The design and psychometric methodology of the National Assessment of Educational Progress (NAEP) is constantly evolving to meet the changing interests and demands stemming from a rapidly shifting educational landscape. NAEP has been built on strong research foundations that include conducting extensive evaluations and comparisons before new…
Descriptors: National Competency Tests, Psychometrics, Statistical Analysis, Computation
Jiang, Yu; Zhang, Jiahui; Xin, Tao – Journal of Educational and Behavioral Statistics, 2019
This article is an overview of the National Assessment of Education Quality (NAEQ) of China in reading, mathematics, sciences, arts, physical education, and moral education at Grades 4 and 8. After a review of the background and history of NAEQ, we present the assessment framework with students' holistic development at the core and the design for…
Descriptors: Foreign Countries, Educational Quality, Educational Improvement, National Competency Tests
Andrich, David; Hagquist, Curt – Journal of Educational and Behavioral Statistics, 2012
The literature in modern test theory on procedures for identifying items with differential item functioning (DIF) among two groups of persons includes the Mantel-Haenszel (MH) procedure. Generally, it is not recognized explicitly that if there is real DIF in some items which favor one group, then as an artifact of this procedure, artificial DIF…
Descriptors: Test Bias, Test Items, Item Response Theory, Statistical Analysis
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
Longford, Nicholas T. – Journal of Educational and Behavioral Statistics, 2014
A method for medical screening is adapted to differential item functioning (DIF). Its essential elements are explicit declarations of the level of DIF that is acceptable and of the loss function that quantifies the consequences of the two kinds of inappropriate classification of an item. Instead of a single level and a single function, sets of…
Descriptors: Test Items, Test Bias, Simulation, Hypothesis Testing
Andrich, David; Marais, Ida; Humphry, Stephen – Journal of Educational and Behavioral Statistics, 2012
Andersen (1995, 2002) proves a theorem relating variances of parameter estimates from samples and subsamples and shows its use as an adjunct to standard statistical analyses. The authors show an application where the theorem is central to the hypothesis tested, namely, whether random guessing to multiple choice items affects their estimates in the…
Descriptors: Test Items, Item Response Theory, Multiple Choice Tests, Guessing (Tests)
Schuster, Christof; Yuan, Ke-Hai – Journal of Educational and Behavioral Statistics, 2011
Because of response disturbances such as guessing, cheating, or carelessness, item response models often can only approximate the "true" individual response probabilities. As a consequence, maximum-likelihood estimates of ability will be biased. Typically, the nature and extent to which response disturbances are present is unknown, and, therefore,…
Descriptors: Computation, Item Response Theory, Probability, Maximum Likelihood Statistics
Smithson, Michael; Merkle, Edgar C.; Verkuilen, Jay – Journal of Educational and Behavioral Statistics, 2011
This paper describes the application of finite-mixture general linear models based on the beta distribution to modeling response styles, polarization, anchoring, and priming effects in probability judgments. These models, in turn, enhance our capacity for explicitly testing models and theories regarding the aforementioned phenomena. The mixture…
Descriptors: Priming, Research Methodology, Probability, Item Response Theory
Wang, Xiaohui; Bradlow, Eric T.; Wainer, Howard; Muller, Eric S. – Journal of Educational and Behavioral Statistics, 2008
In the course of screening a form of a medical licensing exam for items that function differentially (DIF) between men and women, the authors used the traditional Mantel-Haenszel (MH) statistic for initial screening and a Bayesian method for deeper analysis. For very easy items, the MH statistic unexpectedly often found DIF where there was none.…
Descriptors: Bayesian Statistics, Licensing Examinations (Professions), Medicine, Test Items

Roussos, Louis A.; Schnipke, Deborah L.; Pashley, Peter J. – Journal of Educational and Behavioral Statistics, 1999
Derives a general formula for the population parameter being estimated by the Mantel-Haenszel differential item functioning (DIF) statistics. The formula is appropriate for uniform or nonuniform DIF and can be used regardless of the form of the item response function. Shows the relationship between this parameter and item difficulty. (SLD)
Descriptors: Difficulty Level, Estimation (Mathematics), Item Bias, Test Items
van der Linden, Wim J.; Sotaridona, Leonardo – Journal of Educational and Behavioral Statistics, 2006
A statistical test for detecting answer copying on multiple-choice items is presented. The test is based on the exact null distribution of the number of random matches between two test takers under the assumption that the response process follows a known response model. The null distribution can easily be generalized to the family of distributions…
Descriptors: Test Items, Multiple Choice Tests, Cheating, Responses

Camilli, Gregory; Congdon, Peter – Journal of Educational and Behavioral Statistics, 1999
Demonstrates a method for studying differential item functioning (DIF) that can be used with dichotomous or polytomous items and that is valid for data that follow a partial credit Item Response Theory model. A simulation study shows that positively biased Type I error rates are in accord with results from previous studies. (SLD)
Descriptors: Estimation (Mathematics), Item Bias, Item Response Theory, Test Items
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