GDINA R package for cognitive diagnosis analyses
Package website for examples and more information
Watch the NCME digital module 05 for G-DINA model framework and how to use the graphical user interface in the GDINA package
Stable version can be downloaded from R CRAN
Developmental version can be downloaded from github
Distinguishing Features of the GDINA package
ACTCD R package for nonparameteric cognitive diagnosis
Stable version can be downloaded from R CRAN
Package website for examples and more information
Watch the NCME digital module 05 for G-DINA model framework and how to use the graphical user interface in the GDINA package
Stable version can be downloaded from R CRAN
Developmental version can be downloaded from github
Distinguishing Features of the GDINA 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 dignostic tree model
- 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
ACTCD R package for nonparameteric cognitive diagnosis
Stable version can be downloaded from R CRAN