Package: GDINA 2.11.4

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).

Authors:Wenchao Ma [aut, cre, cph], Jimmy de la Torre [aut, cph], Miguel Sorrel [ctb], Zhehan Jiang [ctb], Pablo Najera [ctb]

GDINA_2.11.4.tar.gz
GDINA_2.11.4.zip(r-4.7)GDINA_2.11.4.zip(r-4.6)GDINA_2.11.4.zip(r-4.5)
GDINA_2.11.4.tgz(r-4.6-x86_64)GDINA_2.11.4.tgz(r-4.6-arm64)GDINA_2.11.4.tgz(r-4.5-x86_64)GDINA_2.11.4.tgz(r-4.5-arm64)
GDINA_2.11.4.tar.gz(r-4.7-arm64)GDINA_2.11.4.tar.gz(r-4.7-x86_64)GDINA_2.11.4.tar.gz(r-4.6-arm64)GDINA_2.11.4.tar.gz(r-4.6-x86_64)
GDINA_2.11.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
GDINA/json (API)
NEWS

# Install 'GDINA' in R:
install.packages('GDINA', repos = c('https://wenchao-ma.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/wenchao-ma/gdina/issues

Pkgdown/docs site:https://wenchao-ma.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cdmcognitive-diagnosisdcmdina-modeldinoestimation-modelsgdinaitem-response-theorypsychometricsopenblascpp

9.52 score 32 stars 6 packages 164 scripts 1.0k downloads 15 mentions 38 exports 57 dependencies

Last updated from:a9dc30a55b. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK294
linux-devel-x86_64OK294
source / vignettesOK381
linux-release-arm64OK336
linux-release-x86_64OK305
macos-release-arm64OK183
macos-release-x86_64OK546
macos-oldrel-arm64OK216
macos-oldrel-x86_64OK543
windows-develOK340
windows-releaseOK271
windows-oldrelOK273
wasm-releaseOK219

Exports:att.structureattributepatternautoGDINAbdiagMatrixbootSECAcjointClassRateCMdesignmatrixdifDTMextractGDINAGMSCDMILCAindlogLikindlogPostitemfititemfitPDitemparmLC2LGMCmodelmodelcompmodelfitmonochecknparpersonparmQvalrowMatchscoresimDTMsimGDINAstartGDINAThreeStepCovThreeStepDistalunique_onlyunrestrQ

Dependencies:alabamabase64encbslibcachemclicodetoolscommonmarkcpp11digestfarverfastmapfontawesomeforeachfsfuturefuture.applyggplot2globalsgluegtablehtmltoolshttpuvisobanditeratorsjquerylibjsonlitelabelinglaterlifecyclelistenvmagrittrMASSmemoisemimenloptrnumDerivotelparallellypromisesR6rappdirsRColorBrewerRcppRcppArmadillorlangRsolnpS7sassscalesshinyshinydashboardsourcetoolstruncnormvctrsviridisLitewithrxtable

A quick reference to GDINA R package

Rendered fromGDINA.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2026-05-18
Started: 2018-08-15

Readme and manuals

Help Manual

Help pageTopics
The Generalized DINA Model FrameworkGDINA-package
Generate hierarchical attribute structuresatt.structure
Generate all possible attribute patternsattributepattern
Q-matrix validation, model selection and calibration in one runautoGDINA summary.autoGDINA
Create a block diagonal matrixbdiagMatrix
Calculating standard errors and variance-covariance matrix using bootstrap methodsbootSE
Calculate classification accuracyCA
Combine R Objects by Columnscjoint
Classification Rate EvaluationClassRate
Calculate Misclassification MatricesCM
Generate design matrixdesignmatrix
Differential item functioning for cognitive diagnosis modelsdif summary.dif
Diagnostic multiple-strategy CDMsDTM
extract elements from objects of various classesextract
CDM calibration under the G-DINA model frameworkanova.GDINA coef.GDINA deviance.GDINA extract.GDINA GDINA indlogLik.GDINA indlogPost.GDINA logLik.GDINA nobs.GDINA npar.GDINA personparm.GDINA summary.GDINA vcov.GDINA
Estimating multiple-strategy cognitive diagnosis modelsGMSCDM
Iterative latent-class analysisILCA
Extract log-likelihood for each individualindlogLik
Extract log posterior for each individualindlogPost
Item fit statisticsextract.itemfit itemfit summary.itemfit
Item fit statistics from the power-divergence familyitemfitPD
extract item parameters (deprecated)itemparm itemparm.GDINA
Transformation between latent classes and latent groupsLC2LG
Multiple-choice modelsMCmodel
Item-level model comparison using Wald, LR or LM testsextract.modelcomp modelcomp summary.modelcomp
Model fit statisticsmodelfit
This function checks if monotonicity is violatedmonocheck
Calculate the number of parametersnpar
calculate person (incidental) parameterspersonparm
Create plots for GDINA estimatesplot.GDINA
Item fit plotsplot.itemfit
Mesa plot for Q-matrix validationplot.Qval
Q-matrix validationextract.Qval Qval summary.Qval
Examination for the Certificate of Proficiency in English (ECPE) datarealdata_ECPE
Tatsuoka's fraction subtraction datarealdata_Tatsuoka1990
Count the frequency of a row vector in a data framerowMatch
Score functionscore
Simulated data (10 items, G-DINA model)sim10GDINA
Simulated data (10 items, MC-DINA model)sim10MCDINA
Simulated data (10 items, MC-DINA model)sim10MCDINA2
Simulated data (20 items, sequential G-DINA model)sim20seqGDINA
Simulated data (21 items, sequential DINA model)sim21seqDINA
Simulated data (30 items, DINA model)sim30DINA
Simulated data (30 items, G-DINA model)sim30GDINA
Simulated data (30 items, polytomous G-DINA model)sim30pGDINA
Simulating data for diagnostic tree modelsimDTM
Data simulation based on the G-DINA modelsextract.simGDINA simGDINA
Graphical user interface of the GDINA functionstartGDINA
Three-step ML correction for covariate regressionThreeStepCov
Three-step distal outcome analysisThreeStepDistal
Unique values in a vectorunique_only
Generate unrestricted Qc matrix from an restricted Qc matrixunrestrQ