Qval: The Q-Matrix Validation Methods Framework (original) (raw)
Provide a variety of Q-matrix validation methods for the generalized cognitive diagnosis models, including the method based on the generalized deterministic input, noisy, and gate model (G-DINA) by de la Torre (2011) <doi:10.1007/s11336-011-9207-7> discrimination index (the GDI method) by de la Torre and Chiu (2016) <doi:10.1007/s11336-015-9467-8>, the Hull method by Najera et al. (2021) <doi:10.1111/bmsp.12228>, the stepwise Wald test method (the Wald method) by Ma and de la Torre (2020) <doi:10.1111/bmsp.12156>, the multiple logistic regression‑based Q‑matrix validation method (the MLR-B method) by Tu et al. (2022) <doi:10.3758/s13428-022-01880-x>, the beta method based on signal detection theory by Li and Chen (2024) <doi:10.1111/bmsp.12371> and Q-matrix validation based on relative fit index by Chen et al. (2013) <doi:10.1111/j.1745-3984.2012.00185.x>. Different research methods and iterative procedures during Q-matrix validating are available <doi:10.3758/s13428-024-02547-5>.
Version: | 1.2.3 |
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Depends: | R (≥ 4.1.0) |
Imports: | glmnet, GDINA, MASS, Matrix, nloptr, Rcpp, parallel, plyr |
LinkingTo: | Rcpp |
Published: | 2025-06-02 |
DOI: | 10.32614/CRAN.package.Qval |
Author: | Haijiang Qin |
Maintainer: | Haijiang Qin |
License: | GPL-3 |
URL: | https://haijiangqin.com/Qval/ |
NeedsCompilation: | yes |
Materials: | NEWS |
CRAN checks: | Qval results |
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