README.Rmd

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output: github_document
---

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knitr::opts_chunk$set(
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# simcdm 

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

## Installation

You can install simcdm from GitHub with:

```{r}
#| label: gh-installation
#| eval: false
# install.packages("devtools")
devtools::install_github("tmsalab/simcdm")
```

## Usage

To use `simcdm`, load the package using:

```{r}
#| label: example
#| eval: false
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](https://www.rstudio.com). At
a later time, the `attribute_*()` will likely be moved to a different package.

For more details, please see the [package vignettes](vignettes/):

- [Overview of `simcdm`](https://tmsalab.github.io/simcdm/articles/overview-simcdm.html)
- [Using `simcdm` in R packages](https://tmsalab.github.io/simcdm/articles/simcdm-in-packages.html)

## 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_:

```{r, eval = FALSE}
citation("simcdm")
```

## License

GPL (>= 2)