GDINA: The Generalized DINA Model Framework

A set of psychometric tools for cognitive diagnosis modeling based on the generalized deterministic inputs, noisy and gate (G-DINA) model by de la Torre (2011) <doi:10.1007/s11336-011-9207-7> and its extensions, including the sequential G-DINA model by Ma and de la Torre (2016) <doi:10.1111/bmsp.12070> for polytomous responses, and the polytomous G-DINA model by Chen and de la Torre <doi:10.1177/0146621613479818> for polytomous attributes. Joint attribute distribution can be independent, saturated, higher-order, loglinear smoothed or structured. Q-matrix validation, item and model fit statistics, model comparison at test and item level and differential item functioning can also be conducted. A graphical user interface is also provided. For tutorials, please check Ma and de la Torre (2020) <doi:10.18637/jss.v093.i14>, Ma and de la Torre (2019) <doi:10.1111/emip.12262>, Ma (2019) <doi:10.1007/978-3-030-05584-4_29> and de la Torre and Akbay (2019).

Version: 2.9.4
Depends: R (≥ 3.1.0)
Imports: alabama, graphics, ggplot2, MASS, numDeriv, nloptr, Rcpp (≥ 0.12.1), Rsolnp, stats, shiny, shinydashboard, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: CDM, cdmTools, Matrix, testthat, poLCA, stringr, knitr, rmarkdown
Published: 2023-07-01
DOI: 10.32614/CRAN.package.GDINA
Author: Wenchao Ma [aut, cre, cph], Jimmy de la Torre [aut, cph], Miguel Sorrel [ctb], Zhehan Jiang [ctb]
Maintainer: Wenchao Ma < at>
License: GPL-3
NeedsCompilation: yes
Citation: GDINA citation info
Materials: README NEWS
In views: Psychometrics
CRAN checks: GDINA results


Reference manual: GDINA.pdf
Vignettes: A quick reference to GDINA R package


Package source: GDINA_2.9.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): GDINA_2.9.4.tgz, r-oldrel (arm64): GDINA_2.9.4.tgz, r-release (x86_64): GDINA_2.9.4.tgz, r-oldrel (x86_64): GDINA_2.9.4.tgz
Old sources: GDINA archive

Reverse dependencies:

Reverse imports: ACTCD, cdcatR, cdmTools, LTCDM, Qval
Reverse suggests: dcm2
Reverse enhances: CDM


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