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Assessment of Differential Item Functioning under Cognitive Diagnosis Models: The DINA Model Example
Li, Xiaomin; Wang, Wen-Chung – Journal of Educational Measurement, 2015
The assessment of differential item functioning (DIF) is routinely conducted to ensure test fairness and validity. Although many DIF assessment methods have been developed in the context of classical test theory and item response theory, they are not applicable for cognitive diagnosis models (CDMs), as the underlying latent attributes of CDMs are…
Descriptors: Test Bias, Models, Cognitive Measurement, Evaluation Methods
Huang, Hung-Yu; Wang, Wen-Chung – Journal of Educational Measurement, 2014
The DINA (deterministic input, noisy, and gate) model has been widely used in cognitive diagnosis tests and in the process of test development. The outcomes known as slip and guess are included in the DINA model function representing the responses to the items. This study aimed to extend the DINA model by using the random-effect approach to allow…
Descriptors: Models, Guessing (Tests), Probability, Ability
Hung, Lai-Fa; Wang, Wen-Chung – Journal of Educational and Behavioral Statistics, 2012
In the human sciences, ability tests or psychological inventories are often repeatedly conducted to measure growth. Standard item response models do not take into account possible autocorrelation in longitudinal data. In this study, the authors propose an item response model to account for autocorrelation. The proposed three-level model consists…
Descriptors: Item Response Theory, Correlation, Models, Longitudinal Studies
Huang, Hung-Yu; Wang, Wen-Chung – Educational and Psychological Measurement, 2013
Both testlet design and hierarchical latent traits are fairly common in educational and psychological measurements. This study aimed to develop a new class of higher order testlet response models that consider both local item dependence within testlets and a hierarchy of latent traits. Due to high dimensionality, the authors adopted the Bayesian…
Descriptors: Item Response Theory, Models, Bayesian Statistics, Computation
Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming – Applied Psychological Measurement, 2013
Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…
Descriptors: Item Response Theory, Models, Vertical Organization, Bayesian Statistics
Huang, Hung-Yu; Wang, Wen-Chung – Educational and Psychological Measurement, 2014
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Computation, Test Reliability