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Showing 1 to 15 of 80 results Save | Export
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Mostafa Hosseinzadeh; Ki Lynn Matlock Cole – Educational and Psychological Measurement, 2024
In real-world situations, multidimensional data may appear on large-scale tests or psychological surveys. The purpose of this study was to investigate the effects of the quantity and magnitude of cross-loadings and model specification on item parameter recovery in multidimensional Item Response Theory (MIRT) models, especially when the model was…
Descriptors: Item Response Theory, Models, Maximum Likelihood Statistics, Algorithms
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Yuan, Lu; Huang, Yingshi; Li, Shuhang; Chen, Ping – Journal of Educational Measurement, 2023
Online calibration is a key technology for item calibration in computerized adaptive testing (CAT) and has been widely used in various forms of CAT, including unidimensional CAT, multidimensional CAT (MCAT), CAT with polytomously scored items, and cognitive diagnostic CAT. However, as multidimensional and polytomous assessment data become more…
Descriptors: Computer Assisted Testing, Adaptive Testing, Computation, Test Items
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Wind, Stefanie A. – Educational and Psychological Measurement, 2022
Researchers frequently use Mokken scale analysis (MSA), which is a nonparametric approach to item response theory, when they have relatively small samples of examinees. Researchers have provided some guidance regarding the minimum sample size for applications of MSA under various conditions. However, these studies have not focused on item-level…
Descriptors: Nonparametric Statistics, Item Response Theory, Sample Size, Test Items
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Novak, Josip; Rebernjak, Blaž – Measurement: Interdisciplinary Research and Perspectives, 2023
A Monte Carlo simulation study was conducted to examine the performance of [alpha], [lambda]2, [lambda][subscript 4], [lambda][subscript 2], [omega][subscript T], GLB[subscript MRFA], and GLB[subscript Algebraic] coefficients. Population reliability, distribution shape, sample size, test length, and number of response categories were varied…
Descriptors: Monte Carlo Methods, Evaluation Methods, Reliability, Simulation
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Henninger, Mirka; Debelak, Rudolf; Strobl, Carolin – Educational and Psychological Measurement, 2023
To detect differential item functioning (DIF), Rasch trees search for optimal split-points in covariates and identify subgroups of respondents in a data-driven way. To determine whether and in which covariate a split should be performed, Rasch trees use statistical significance tests. Consequently, Rasch trees are more likely to label small DIF…
Descriptors: Item Response Theory, Test Items, Effect Size, Statistical Significance
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Paek, Insu; Lin, Zhongtian; Chalmers, Robert Philip – Educational and Psychological Measurement, 2023
To reduce the chance of Heywood cases or nonconvergence in estimating the 2PL or the 3PL model in the marginal maximum likelihood with the expectation-maximization (MML-EM) estimation method, priors for the item slope parameter in the 2PL model or for the pseudo-guessing parameter in the 3PL model can be used and the marginal maximum a posteriori…
Descriptors: Models, Item Response Theory, Test Items, Intervals
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Cai, Liuhan; Albano, Anthony D.; Roussos, Louis A. – Measurement: Interdisciplinary Research and Perspectives, 2021
Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item…
Descriptors: Adaptive Testing, Test Items, Item Response Theory, Test Construction
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Sahin Kursad, Merve; Cokluk Bokeoglu, Omay; Cikrikci, Rahime Nukhet – International Journal of Assessment Tools in Education, 2022
Item parameter drift (IPD) is the systematic differentiation of parameter values of items over time due to various reasons. If it occurs in computer adaptive tests (CAT), it causes errors in the estimation of item and ability parameters. Identification of the underlying conditions of this situation in CAT is important for estimating item and…
Descriptors: Item Analysis, Computer Assisted Testing, Test Items, Error of Measurement
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Fu, Yanyan; Strachan, Tyler; Ip, Edward H.; Willse, John T.; Chen, Shyh-Huei; Ackerman, Terry – International Journal of Testing, 2020
This research examined correlation estimates between latent abilities when using the two-dimensional and three-dimensional compensatory and noncompensatory item response theory models. Simulation study results showed that the recovery of the latent correlation was best when the test contained 100% of simple structure items for all models and…
Descriptors: Item Response Theory, Models, Test Items, Simulation
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Gurdil Ege, Hatice; Demir, Ergul – Eurasian Journal of Educational Research, 2020
Purpose: The present study aims to evaluate how the reliabilities computed using a, Stratified a, Angoff-Feldt, and Feldt-Raju estimators may differ when sample size (500, 1000, and 2000) and item type ratio of dichotomous to polytomous items (2:1; 1:1, 1:2) included in the scale are varied. Research Methods: In this study, Cronbach's a,…
Descriptors: Test Format, Simulation, Test Reliability, Sample Size
Derek Sauder – ProQuest LLC, 2020
The Rasch model is commonly used to calibrate multiple choice items. However, the sample sizes needed to estimate the Rasch model can be difficult to attain (e.g., consider a small testing company trying to pretest new items). With small sample sizes, auxiliary information besides the item responses may improve estimation of the item parameters.…
Descriptors: Item Response Theory, Sample Size, Computation, Test Length
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Kárász, Judit T.; Széll, Krisztián; Takács, Szabolcs – Quality Assurance in Education: An International Perspective, 2023
Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…
Descriptors: Test Length, Probability, Comparative Analysis, Difficulty Level
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Koziol, Natalie A.; Goodrich, J. Marc; Yoon, HyeonJin – Educational and Psychological Measurement, 2022
Differential item functioning (DIF) is often used to examine validity evidence of alternate form test accommodations. Unfortunately, traditional approaches for evaluating DIF are prone to selection bias. This article proposes a novel DIF framework that capitalizes on regression discontinuity design analysis to control for selection bias. A…
Descriptors: Regression (Statistics), Item Analysis, Validity, Testing Accommodations
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Saatcioglu, Fatima Munevver; Atar, Hakan Yavuz – International Journal of Assessment Tools in Education, 2022
This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…
Descriptors: Accuracy, Classification, Item Response Theory, Programming Languages
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Lu, Ru; Guo, Hongwen; Dorans, Neil J. – ETS Research Report Series, 2021
Two families of analysis methods can be used for differential item functioning (DIF) analysis. One family is DIF analysis based on observed scores, such as the Mantel-Haenszel (MH) and the standardized proportion-correct metric for DIF procedures; the other is analysis based on latent ability, in which the statistic is a measure of departure from…
Descriptors: Robustness (Statistics), Weighted Scores, Test Items, Item Analysis
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