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

Visit the package websitehttps://wenchao-ma.github.io/GDINA/ forexamples, tutorials and more information.

• WatchMa and de la Torre’s (2019) NCME digital module5 on a gentle introductionto the G-DINA model framework and the use of graphical userinterface for CDM analyses

• Checkthe book chapter by Ma(2019) on anintroduction to the GDINA package

• Checkde la Torre and Akbay’s (2019) articleon how to conduct various CDM analyses using the graphical userinterface

• CheckShi, et al (2021) onhow to use this package, along with other R packages for CDManalyses

• Estimating G-DINA model and a variety of widely-used models subsumedby the G-DINA model, including the DINA model, DINO model,additive-CDM (A-CDM), linear logistic model (LLM), reducedreparametrized unified model (RRUM), multiple-strategy DINA modelfor dichotomous responses
• Estimating models within the G-DINA model framework usinguser-specified design matrix and link functions
• Estimating Bugs-DINA, DINO and G-DINA models for dichotomousresponses
• Estimating sequential G-DINA model for ordinal and nominal responses
• Estimating the generalized multiple-strategy cognitive diagnosismodels (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 likelihoodratio test
• Simulating data based on all aforementioned CDMs
• Providing graphical user interface for users less familiar with R

The stable version of GDINA should be installed from R CRAN athere

To install this package from source:

1. Windows users may need to install theRtools and includethe checkbox option of installing Rtools to their path for easiercommand line usage. Mac users will have to download the necessarytools from theXcode andits related command line tools (found within Xcode’s Preference Paneunder Downloads/Components); most Linux distributions should alreadyhave up to date compilers (or if not they can be updated easily).

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

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