Conditional Independence and Dimensionality of Cognitive Diagnostic Models: a Test for Model Fit
Publication Date
2019
Journal Title
J Classification
Abstract
© 2019, The Classification Society. Nonparametric cognitive diagnosis methods are useful in cognitive diagnosis modeling for calibration efficiency, especially when sample size is small or large, or the latent attributes are more complex. This article proposes the Mantel-Haenszel chi-squared statistic as an index for detecting the misspecification of latent attributes as well as testlet effects in nonparametric cognitive diagnosis methods. The proposed theoretical considerations are augmented by simulation studies conducted to assess the performance of the Mantel-Haenszel statistic under various conditions within the nonparametric diagnosis framework, with a special focus on situations were the set of latent abilities assumed to underlie the data was underspecified.
Volume Number
36
Pages
295–305
Document Type
Article
Status
Faculty
Facility
School of Medicine
Primary Department
Science Education
DOI
10.1007/s00357-018-9287-5
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