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https://github.com/tmsalab/cirt

Jointly model the accuracy of cognitive responses and item choices within a bayesian hierarchical framework as described by Culpepper and Balamuta (2015) <doi:10.1007/s11336-015-9484-7>. In addition, the package contains the datasets used within the analysis of the paper.
https://github.com/tmsalab/cirt

armadillo bayesian choice cognitive-diagnostic-models gibbs-sampling item-response-theory r rcpparmadillo rstats

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Jointly model the accuracy of cognitive responses and item choices within a bayesian hierarchical framework as described by Culpepper and Balamuta (2015) <doi:10.1007/s11336-015-9484-7>. In addition, the package contains the datasets used within the analysis of the paper.

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README

          

---
output: github_document
---

```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```

# cIRT: Choice Item Response Theory

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Jointly model the accuracy of cognitive responses and item choices
within a Bayesian hierarchical framework as described by Culpepper and
Balamuta (2015).

## Installation

You can install `cIRT` from CRAN using:

```{r cran-installation, eval = FALSE}
install.packages("cIRT")
```

Or, you can be on the cutting-edge development version on GitHub using:

```{r gh-installation, eval = FALSE}
if(!requireNamespace("devtools")) install.packages("devtools")
devtools::install_github("tmsalab/cIRT")
```

## Usage

To use the `cIRT` package, load it into _R_ using:

```{r example, message = FALSE}
library("cIRT")
```

## Authors

Steven Andrew Culpepper and James Joseph Balamuta

## Citing the cIRT package

To ensure future development of the package, please cite `cIRT`
package if used during an analysis or simulation studies. Citation information
for the package may be acquired by using in *R*:

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

## License

GPL (>= 2)