Qval: The Q-Matrix Validation Methods Framework

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 step-wise Wald test method (the Wald method) by Ma and de la Torre (2020) <DOI:10.1111/bmsp.12156>, the Hull method by Najera et al. (2021) <DOI:10.1111/bmsp.12228>, 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 la. (2013) <DOI:10.1111/j.1745-3984.2012.00185.x>. Different research methods and iterative procedures during Q-matrix validating are available.

Getting started

Package details

AuthorHaijiang Qin [aut, cre, cph] (<https://orcid.org/0009-0000-6721-5653>), Lei Guo [aut, cph] (<https://orcid.org/0000-0002-8273-3587>)
MaintainerHaijiang Qin <haijiang133@outlook.com>
LicenseGPL-3
Version1.2.0
URL https://haijiangqin.com/Qval/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("Qval")

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Qval documentation built on April 3, 2025, 6:20 p.m.