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Diagnostic Classification Model Data Simulations

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Synopsis

This R package manages the heavy lifting of keeping track of the various data generation algorithms that I am using to do simulation work on CDA models. Currently there are data generation algorithms (in various states of functionality!) for:

  • R-DINA with a simple 2 attribute Q-matrix
  • R-DINA with the Hartz Roussos Q-matrix (low)
  • RUM Hartz Roussos with Q-matrix (low)
  • R-RUM Hartz Roussos with Q-matrix (low)

Included Q-matrices are:

  • Simple Q-matrix (2 attribute, 30 item)
  • Hartz Roussos Q-matrix (Low cognitive complexity; 7 attribute, 40 item)

This is very much a work in progress! The goal is to have fully functional algorithms that are fully tested using testthat. The current code coverage levels may or may not indicate completeness/quality of tests (yet).

Code Example

q <- hartzRoussosQ() data <- rDINASimpleQ(500)

Motivation

Simulation work is hard enough without having to worry about managing and testing the data simulation algorithms.

Installation

Install using devtools using the repo URL.

Tests

Test run as part of a CI environment using testthat.

Contributors

Dave Rackham ddrackham@gmail.com

License

MIT License (see License.txt)

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