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GDINA Package for Cognitive Diagnosis Modelling

How to cite the package

Ma, W. & de la Torre, J. (2019). GDINA: The generalized DINA model framework. R package version 2.4. Retrived from https://CRAN.R-project.org/package=GDINA

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

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)
  • 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

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")

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

Upcoming Training Sessions

  • Cognitive Diagnosis Modeling: A General Framework Approach and Its Implementation in R - A NCME training session on April 4, 2019 - see here

Past Training Sessions

  • Frontiers in Educational Measurement pre-conference workshop on September 11, 2018 at the University of Oslo - see here
  • 13th Cross-Strait Conference on Educational and Psychological Testing pre-conference workshop on Oct 18, 2018 - see here
  • NCME training session on April 12, 2018 - see here
  • NCME training session on April 26, 2017
  • Workshop at the Brazil Congress of Item Response Theory November 30-December 1, 2016
  • Pre-conference short course in the Fourth Conference on the Statistical Methods in Psychometrics from August 30 to September 1, 2016 at Columbia University here

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Version

Install

install.packages('GDINA')

Monthly Downloads

961

Version

2.4.0

License

GPL-3

Issues

0

Pull Requests

1

Stars

30

Forks

12

Maintainer

Wenchao Ma

Last Published

March 11th, 2019

Functions in GDINA (2.4.0)

DTM

Experimental function for diagnostic multiple-strategy CDMs
att.structure

Generate hierarchical attribute structures
attributepattern

Generate all possible attribute patterns
extract

extract elements from objects of various classes
ecpe

Examination for the Certificate of Proficiency in English (ECPE) data
designmatrix

Generate design matrix
indlogPost

Extract log posterior for each individual
dif

Differential item functioning for cognitive diagnosis models
modelcomp

Item-level model comparison using Wald, LR or LM tests
internal_GDINA

Functions for internal use
modelfit

Model fit statistics
plot.Qval

Mesa plot for Q-matrix validation
plot.itemfit

Item fit plots
GDINA

CDM calibration under the G-DINA model framework
GMSCDM

Estimating multiple-strategy cognitive diagnosis models
sim30GDINA

Simulated data (30 items, G-DINA model)
sim30pGDINA

Simulated data (30 items, polytomous G-DINA model)
ClassRate

Classification Rate Evaluation
CA

Calculate classification accuracy
frac20

Tatsuoka's fraction subtraction data
indlogLik

Extract log-likelihood for each individual
personparm

calculate person (incidental) parameters
plot.GDINA

Create plots for GDINA estimates
sim21seqDINA

Simulated data (21 items, sequential DINA model)
sim30DINA

Simulated data (30 items, DINA model)
startGDINA

Graphical user interface of the GDINA function
unique_only

Unique values in a vector
bootSE

Calculating standard errors and variance-covariance matrix using bootstrap methods
cjoint

Combine R Objects by Columns
monocheck

This function checks if monotonicity is violated
npar

Calculate the number of parameters
rowMatch

Count the frequency of a row vector in a data frame
LC2LG

Transformation between latent classes and latent groups
score

Score function
unrestrQ

Generate unrestricted Qc matrix from an restricted Qc matrix
Qval

Q-matrix validation
autoGDINA

Q-matrix validation, model selection and calibration in one run
bdiagMatrix

Create a block diagonal matrix
itemfit

Item fit statistics
itemparm

extract item parameters (deprecated)
sim10GDINA

Simulated data (10 items, G-DINA model)
simDTM

Simulating data for diagnostic tree model
simGDINA

Data simulation based on the G-DINA models
sim20seqGDINA

Simulated data (20 items, sequential G-DINA model)
GDINA-package

The Generalized DINA Model Framework