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Direct linkJang, Yoonsun; Kim, Seock-Ho; Cohen, Allan S. – Journal of Educational Measurement, 2018
This study investigates the effect of multidimensionality on extraction of latent classes in mixture Rasch models. In this study, two-dimensional data were generated under varying conditions. The two-dimensional data sets were analyzed with one- to five-class mixture Rasch models. Results of the simulation study indicate the mixture Rasch model…
Descriptors: Item Response Theory, Simulation, Correlation, Multidimensional Scaling
Feuerstahler, Leah; Wilson, Mark – Journal of Educational Measurement, 2019
Scores estimated from multidimensional item response theory (IRT) models are not necessarily comparable across dimensions. In this article, the concept of aligned dimensions is formalized in the context of Rasch models, and two methods are described--delta dimensional alignment (DDA) and logistic regression alignment (LRA)--to transform estimated…
Descriptors: Item Response Theory, Models, Scores, Comparative Analysis
Download full textÖztürk-Gübes, Nese; Kelecioglu, Hülya – Educational Sciences: Theory and Practice, 2016
The purpose of this study was to examine the impact of dimensionality, common-item set format, and different scale linking methods on preserving equity property with mixed-format test equating. Item response theory (IRT) true-score equating (TSE) and IRT observed-score equating (OSE) methods were used under common-item nonequivalent groups design.…
Descriptors: Test Format, Item Response Theory, True Scores, Equated Scores
Walker, Cindy M.; Azen, Razia; Schmitt, Thomas – Educational and Psychological Measurement, 2006
It is believed by some that most tests are multidimensional, meaning that they measure more than one underlying construct. The primary objective of this study is to illustrate how variations in the secondary ability distribution affect the statistical detection of dimensionality and to demonstrate the difference between substantive and statistical…
Descriptors: Multidimensional Scaling, Item Response Theory, Comparative Testing, Statistical Analysis
Gierl, Mark J.; Leighton, Jacqueline P.; Tan, Xuan – Journal of Educational Measurement, 2006
DETECT, the acronym for Dimensionality Evaluation To Enumerate Contributing Traits, is an innovative and relatively new nonparametric dimensionality assessment procedure used to identify mutually exclusive, dimensionally homogeneous clusters of items using a genetic algorithm ( Zhang & Stout, 1999). Because the clusters of items are mutually…
Descriptors: Program Evaluation, Cluster Grouping, Evaluation Methods, Multivariate Analysis
Wang, Wen-Chung; Wilson, Mark; Shih, Ching-Lin – Journal of Educational Measurement, 2006
This study presents the random-effects rating scale model (RE-RSM) which takes into account randomness in the thresholds over persons by treating them as random-effects and adding a random variable for each threshold in the rating scale model (RSM) (Andrich, 1978). The RE-RSM turns out to be a special case of the multidimensional random…
Descriptors: Item Analysis, Rating Scales, Item Response Theory, Monte Carlo Methods
