Incorporating student covariates in cognitive diagnosis models

DOI10.1007/s00357-013-9130-yzbMath1360.62520OpenAlexW2168749265WikidataQ60655821 ScholiaQ60655821MaRDI QIDQ269217

Elizabeth Ayers, Sophia Rabe-Hesketh, Rebecca Nugent

Publication date: 18 April 2016

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00357-013-9130-y

zbMATH Keywords

covariatesrandom effectcognitive diagnosis modelcollateral informationconcomitant variablesDIFDINAhigher order modelskill diagnosis

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to psychology (62P15)

Related Items (2)

Extending exploratory diagnostic classification models: Inferring the effect of covariates ⋮ A partial mastery, higher-order latent structural model for polytomous attributes in cognitive diagnostic assessments

Uses Software

• R
• WinBUGS
• Stata
• Mplus
• BUGS

Cites Work

• Unnamed Item
• Cluster analysis for cognitive diagnosis: theory and applications
• A generalized Rasch model for manifest predictors
• Measurement invariance, factor analysis and factorial invariance
• Estimating multiple classification latent class models
• Higher-order latent trait models for cognitive diagnosis
• Simultaneous factor analysis in several populations
• Latent Structure Analysis of a Set of Multidimensional Contingency Tables
• Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable
• Concomitant variables in finite mixture models
• Interpreting Parameters in the Logistic Regression Model with Random Effects

This page was built for publication: Incorporating student covariates in cognitive diagnosis models