Balancing fit and parsimony to improve Q‐matrix validation-Reference-Cited by-同舟云学术

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Balancing fit and parsimony to improve Q‐matrix validation

Published:2020-11-24 Issue:S1 Volume:74 Page:110-130
ISSN:0007-1102
Container-title:British Journal of Mathematical and Statistical Psychology
language:en
Short-container-title:Br J Math Stat Psychol

Author:

Nájera Pablo¹^ORCID,Sorrel Miguel A.¹^ORCID,Torre Jimmy²,Abad Francisco José¹^ORCID

Affiliation:

1. Department of Social Psychology and Methodology Autonomous University of Madrid Spain

2. Faculty of Education The University of Hong Kong Pokfulam Hong Kong

Funder

European Social Fund

Publisher

Wiley

Subject

General Psychology,Arts and Humanities (miscellaneous),General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/bmsp.12228

Reference28 articles.

1. Selecting among three-mode principal component models of different types and complexities: A numerical convex hull based method

2. A Procedure for Diagnostically Modeling Extant Large-Scale Assessment Data: The Case of the Programme for International Student Assessment in Reading

3. The Generalized DINA Model Framework

4. A general method of empirical Q‐matrix validation;Torre J.;Psychometrika,2016

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2. Combining regularization and logistic regression model to validate the Q‐matrix for cognitive diagnosis model;British Journal of Mathematical and Statistical Psychology;2024-04-22

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