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The Q-Matrix Anchored Mixture Rasch Model [PDF]
Frontiers in Psychology, 2021 Mixture item response theory (IRT) models include a mixture of latent subpopulations such that there are qualitative differences between subgroups but within each subpopulation the measure model based on a continuous latent variable holds.
Ming-Chi Tseng, Wen-Chung Wang
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Regularized Mixture Rasch Model
Information, 2022 The mixture Rasch model is a popular mixture model for analyzing multivariate binary data. The drawback of this model is that the number of estimated parameters substantially increases with an increasing number of latent classes, which, in turn, hinders ...
Alexander Robitzsch
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Setting a standard for low reading proficiency: A comparison of the bookmark procedure and constrained mixture Rasch model. [PDF]
PLoS ONE, 2021 In order to draw pertinent conclusions about persons with low reading skills, it is essential to use validated standard-setting procedures by which they can be assigned to their appropriate level of proficiency.
Tabea Feseker +2 more
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Different Approaches to Covariate Inclusion in the Mixture Rasch Model. [PDF]
Educ Psychol Meas, 2016 The present study investigates different approaches to adding covariates and the impact in fitting mixture item response theory models. Mixture item response theory models serve as an important methodology for tackling several psychometric issues in test development, including the detection of latent differential item functioning.
Li T, Jiao H, Macready GB.
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Mixture Rasch Model with Main and Interaction Effects of Covariates on Latent Class Membership [PDF]
International Journal of Assessment Tools in Education, 2019 Covariateshave been used in mixture IRT models to help explain why examinees are classedinto different latent classes. Previous research has considered manifestvariables as covariates in a mixture Rasch analysis for prediction of groupmembership.
Tugba Karadavut +2 more
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Flexible Rasch Mixture Models with Package psychomix
Journal of Statistical Software, 2012 Measurement invariance is an important assumption in the Rasch model and mixture models constitute a flexible way of checking for a violation of this assumption by detecting unobserved heterogeneity in item response data.
Hannah Frick +3 more
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Model Selection for Multilevel Mixture Rasch Models [PDF]
Applied Psychological Measurement, 2018 Mixture item response theory (MixIRT) models can sometimes be used to model the heterogeneity among the individuals from different subpopulations, but these models do not account for the multilevel structure that is common in educational and ...
Allan S. Cohen, Sedat Sen, Seock-Ho Kim
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Flexible Rasch Mixture Models with package psychomix [PDF]
Journal of Statistical Software, 2011 Measurement invariance is an important assumption in the Rasch model and mixture models constitute a flexible way of checking for a violation of this assumption by detecting unobserved heterogeneity in item response data.
Frick, H +12 more
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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.
Hakan Yavuz Atar +1 more
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Rasch Mixture Models for DIF Detection: a comparison of old and new score specifications [PDF]
Educational and Psychological Measurement, 2014 Rasch mixture models can be a useful tool when checking the assumption of measurement invariance for a single Rasch model. They provide advantages compared to manifest differential item functioning (DIF) tests when the DIF groups are only weakly ...
Zeileis, Achim +5 more
core +7 more sources