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simcdm

The goal of simcdm is to provide flexible ways to simulate data under cognitive diagnostic models.

Installation

You can install simcdm from GitHub with:

# install.packages("remotes")
remotes::install_github("tmsalab/simcdm")

Usage

To use simcdm, load the package using:

library("simcdm")

Overview

There are four distinct sets of functions within the package:

• Attributes: attribute_classes(), attribute_bijection(), attribute_inv_bijection(), and sim_subject_attributes().
• Matrix: sim_q_matrix() and sim_eta_matrix()
• Deterministic Input, Noisy And Gate (DINA): sim_dina_items() and sim_dina_attributes()
• reduced Reparameterized Unified Model (rRUM): sim_rrum_items()

Functions that use random numbers to simulate values are named with the prefix of sim_*(). This is done to allow for functions to be quickly identified and used through autocomplete inside of the RStudio IDE or VS Code. At a later time, the attribute_*() will likely be moved to a different package.

For more details, please see the package vignettes:

• Overview of simcdm
• Using simcdm in R packages

Authors

James Joseph Balamuta and Steven Andrew Culpepper with contributions from Aaron Hudson.

Citing the simcdm package

To ensure future development of the package, please cite simcdm package if used during the analysis or simulations. Citation information for the package may be acquired by using in R:

citation("simcdm")

License

GPL (>= 2)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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