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Karadavut, Tugba; Cohen, Allan S.; Kim, Seock-Ho – International Journal of Assessment Tools in Education, 2019
Covariates have been used in mixture IRT models to help explain why examinees are classed into different latent classes. Previous research has considered manifest variables as covariates in a mixture Rasch analysis for prediction of group membership. Latent covariates, however, are more likely to have higher correlations with the latent class…
Descriptors: Item Response Theory, Classification, Correlation, International Assessment
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Ölmez, Ibrahim Burak; Cohen, Allan S. – International Journal of Assessment Tools in Education, 2018
The purpose of this study was to investigate a new methodology for detection of differences in middle grades students' math anxiety. A mixture partial credit model analysis was used to detect distinct latent classes based on homogeneities in response patterns. The analysis detected two latent classes. Students in Class 1 had less anxiety about…
Descriptors: Mathematics Anxiety, Middle School Students, At Risk Students, Self Efficacy
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Lee, Sunbok; Choi, Youn-Jeng; Cohen, Allan S. – International Journal of Assessment Tools in Education, 2018
A simulation study is a useful tool in examining how validly item response theory (IRT) models can be applied in various settings. Typically, a large number of replications are required to obtain the desired precision. However, many standard software packages in IRT, such as MULTILOG and BILOG, are not well suited for a simulation study requiring…
Descriptors: Item Response Theory, Simulation, Replication (Evaluation), Automation