Mixture Rasch Model with Main and Interaction Effects of Covariates on Latent Class Membership
Abstract
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 variable. This study investigated effects of
including latent variables as covariates in a mixture Rasch model, in presence
of and in absence of interactions between the covariates. Results indicated the
latent and manifest covariates influenced latent class membership but did not
have much influence on class ability means or class proportions. The influence
was relatively higher for latent covariates compared to manifest covariates.
The effects of the covariates on class membership and on item parameters were
class specific. Substantial effects of covariates on item parameters yielded
smaller standard errors for item parameter estimates. A significant interaction
term also had an effect on the coefficients for predicting and explaining
latent class membership.
Keywords
References
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Details
Primary Language
English
Subjects
Studies on Education
Journal Section
Research Article
Authors
Tugba Karadavut
*
0000-0002-8738-7177
Türkiye
Allan S. Cohen
This is me
0000-0002-8776-9378
United States
Seock-ho Kim
This is me
0000-0002-2353-7826
United States
Publication Date
October 15, 2019
Submission Date
February 21, 2019
Acceptance Date
July 9, 2019
Published in Issue
Year 2019 Volume: 6 Number: 3
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