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ERIC Number: EJ844284
Record Type: Journal
Publication Date: 2009
Pages: 21
Abstractor: As Provided
ISSN: ISSN-0146-6216
Model Selection Methods for Mixture Dichotomous IRT Models
Li, Feiming; Cohen, Allan S.; Kim, Seock-Ho; Cho, Sun-Joo
Applied Psychological Measurement, v33 n5 p353-373 2009
This study examines model selection indices for use with dichotomous mixture item response theory (IRT) models. Five indices are considered: Akaike's information coefficient (AIC), Bayesian information coefficient (BIC), deviance information coefficient (DIC), pseudo-Bayes factor (PsBF), and posterior predictive model checks (PPMC). The five indices provide somewhat different recommendations for a set of real data. Results from a simulation study indicate that BIC selects the correct (i.e., the generating) model well under most conditions simulated and for all three of the dichotomous mixture IRT models considered. PsBF is almost as effective. AIC and PPMC tend to select the more complex model under some conditions. DIC is least effective for this use. (Contains 5 tables.)
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: Elementary Education; Grade 3
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Florida
Identifiers - Assessments and Surveys: Florida Comprehensive Assessment Test