Package: GDINA 2.9.4

Wenchao Ma

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]

GDINA_2.9.4.tar.gz
GDINA_2.9.4.tar.gz(r-4.5-noble)GDINA_2.9.4.tar.gz(r-4.4-noble)
GDINA_2.9.4.tgz(r-4.4-emscripten)GDINA_2.9.4.tgz(r-4.3-emscripten)
GDINA.pdf |GDINA.html
GDINA/json (API)
NEWS

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

Bug tracker:https://github.com/wenchao-ma/gdina/issues1 issues

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

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

On CRAN:

Conda:

openblascpp

5.26 score 2 stars 6 packages 973 downloads 15 mentions 34 exports 58 dependencies

Last updated 2 years agofrom:1900519440. Checks:1 OK, 2 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 23 2025
R-4.5-linux-x86_64NOTEMar 23 2025
R-4.4-linux-x86_64NOTEMar 23 2025

Exports:att.structureattributepatternautoGDINAbdiagMatrixbootSECAcjointClassRatedesignmatrixdifDTMextractGDINAGMSCDMILCAindlogLikindlogPostitemfititemparmLC2LGMCmodelmodelcompmodelfitmonochecknparpersonparmQvalrowMatchscoresimDTMsimGDINAstartGDINAunique_onlyunrestrQ

Dependencies:alabamabase64encbslibcachemclicolorspacecommonmarkcrayondigestfansifarverfastmapfontawesomefsggplot2gluegtablehtmltoolshttpuvisobandjquerylibjsonlitelabelinglaterlatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmenloptrnumDerivpillarpkgconfigpromisesR6rappdirsRColorBrewerRcppRcppArmadillorlangRsolnpsassscalesshinyshinydashboardsourcetoolstibbletruncnormutf8vctrsviridisLitewithrxtable

A quick reference to GDINA R package

Rendered fromGDINA.Rmdusingknitr::rmarkdownon Mar 23 2025.

Last update: 2020-03-01
Started: 2018-10-30

Citation

To cite GDINA in publications use:

Ma W, de la Torre J (2020). “GDINA: An R Package for Cognitive Diagnosis Modeling.” Journal of Statistical Software, 93(14), 1–26. doi:10.18637/jss.v093.i14.

Corresponding BibTeX entry:

  @Article{,
    title = {{GDINA}: An {R} Package for Cognitive Diagnosis Modeling},
    author = {Wenchao Ma and Jimmy {de la Torre}},
    journal = {Journal of Statistical Software},
    year = {2020},
    volume = {93},
    number = {14},
    pages = {1--26},
    doi = {10.18637/jss.v093.i14},
  }

Readme and manuals

GDINA Package for Cognitively Diagnostic Analyses

How to cite the package

Ma, W. & de la Torre, J. (2020). GDINA: An R Package for Cognitive Diagnosis Modeling. Journal of Statistical Software, 93(14), 1-26. https://doi.org/10.18637/jss.v093.i14

Visit the package website https://wenchao-ma.github.io/GDINA/ for examples, tutorials and more information.

Learning resources

Features of the package

  • Estimating G-DINA model and a variety of widely-used models subsumed by the G-DINA model, including the DINA model, DINO model, additive-CDM (A-CDM), linear logistic model (LLM), reduced reparametrized unified model (RRUM), multiple-strategy DINA model for dichotomous responses
  • Estimating models within the G-DINA model framework using user-specified design matrix and link functions
  • Estimating Bugs-DINA, DINO and G-DINA models for dichotomous responses
  • Estimating sequential G-DINA model for ordinal and nominal responses
  • Estimating the generalized multiple-strategy cognitive diagnosis models (experimental)
  • Estimating the diagnostic tree model (experimental)
  • Estimating multiple-choice models
  • Modelling independent, saturated, higher-order, loglinear smoothed, and structured joint attribute distribution
  • Accommodating multiple-group model analysis
  • Imposing monotonic constrained success probabilities
  • Accommodating binary and polytomous attributes
  • Validating Q-matrix under the general model framework
  • Evaluating absolute and relative item and model fit
  • Comparing models at the test and item levels
  • Detecting differential item functioning using Wald and likelihood ratio test
  • Simulating data based on all aforementioned CDMs
  • Providing graphical user interface for users less familiar with R

Installation

The stable version of GDINA should be installed from R CRAN at here

To install this package from source:

  1. Windows users may need to install the Rtools and include the checkbox option of installing Rtools to their path for easier command line usage. Mac users will have to download the necessary tools from the Xcode and its related command line tools (found within Xcode’s Preference Pane under Downloads/Components); most Linux distributions should already have up to date compilers (or if not they can be updated easily).

  2. Install the devtools package (if necessary), and install the package from the Github source code.

# install.packages("devtools")
devtools::install_github("Wenchao-Ma/GDINA")

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
Generate design matrixdesignmatrix
Differential item functioning for cognitive diagnosis modelsdif summary.dif
Experimental function for diagnostic multiple-strategy CDMsDTM
Examination for the Certificate of Proficiency in English (ECPE) dataecpe
extract elements from objects of various classesextract
Tatsuoka's fraction subtraction datafrac20
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
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
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
Unique values in a vectorunique_only
Generate unrestricted Qc matrix from an restricted Qc matrixunrestrQ