Model Selection Methods for Mixture Dichotomous IRT Models

By Feiming Li, Allan S. Cohen, Seock-Ho Kim, Sun-Joo Cho. 2009

168 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f1ba7863291da793436e03a40e23967965f6cee4

How researchers see this paper

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In Management Science and Operations Research

1. J. Patrick Meyer
2. Scott Vrieze

In Statistics and Probability

1. J. Patrick Meyer
2. Scott Vrieze
3. Tal Yarkoni
4. J. Westfall

Citations in the corpus

• A Mixture Rasch Model With Item Response Time Components (2010, methodology): “Simulation studies of the BIC computed in the manner recommended by Congdon have shown that the BIC successfully identifies the MRM with the right number of latent classes (Cho, Cohen, & Kim, 2007; Li et al., 2009).”
• Model selection and psychological theory: A discussion of the differences between the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) (2012, result): “In a study of FMMs with categorical variables (mixture IRT models), F. Li et al. (2009) obtained similar results, although found much greater support for the BIC in the parameter space studied there.”