Journal article
Explanatory Cognitive Diagnostic Models: Incorporating Latent and Observed Predictors
Applied psychological measurement, Vol.42(5), pp.376-392
07/01/2018
DOI: 10.1177/0146621617738012
PMCID: PMC6023094
PMID: 30034055
Abstract
Large-scale educational testing data often contain vast amounts of variables associated with information pertaining to test takers, schools, or access to educational resources—information that can help
explain
relationships between test taker performance and their learning environment. This study examines approaches to incorporate latent and observed explanatory variables as predictors for cognitive diagnostic models (CDMs). Methods to specify and simultaneously estimate observed and latent variables (estimated using item response theory) as predictors affecting attribute mastery were examined. Real-world data analyses were conducted to demonstrate the application using large-scale international testing data. Simulation studies were conducted to examine the recovery and classification for simultaneously estimating multiple latent (using dichotomous and polytomous items as indicators for the latent construct) and observed predictors for varying sample sizes and number of attributes. Results showed stable parameter recovery and consistency in attribute classification. Implications for latent predictors and attribute specifications are discussed.
Details
- Title: Subtitle
- Explanatory Cognitive Diagnostic Models: Incorporating Latent and Observed Predictors
- Creators
- Yoon Soo Park - University of Illinois at ChicagoKuan Xing - University of Illinois at ChicagoYoung-Sun Lee - Columbia University
- Resource Type
- Journal article
- Publication Details
- Applied psychological measurement, Vol.42(5), pp.376-392
- Publisher
- SAGE Publications
- DOI
- 10.1177/0146621617738012
- PMID
- 30034055
- PMCID
- PMC6023094
- ISSN
- 0146-6216
- eISSN
- 1552-3497
- Language
- English
- Date published
- 07/01/2018
- Academic Unit
- Family and Community Medicine; Office of Consultation and Research in Medical Education
- Record Identifier
- 9984658328902771
Metrics
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