README.Rmd

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output: github_document
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# dina

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Estimate the Deterministic Input, Noisy And Gate (DINA) cognitive diagnostic
model parameters using the Gibbs sampler described by Culpepper (2015) 
<doi: 10.3102/1076998615595403>.

## Installation

You can install `dina` from CRAN using:

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

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/dina")
```

## Usage

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

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

From there, the DINA CDM can be estimated using:

```{r dina-est, eval = FALSE}
dina_model = dina(<data>, <q>, chain_length = 10000)
```

To simulate item data under DINA, use:

```{r dina-sim, eval = FALSE}
# Set a seed for reproducibility
set.seed(888)

# Setup Parameters
N = 15   # Number of Examinees / Subjects
J = 10   # Number of Items
K = 2    # Number of Skills / Attributes

# Assign slipping and guessing values for each item
ss = gs = rep(.2, J)

# Simulate identifiable Q matrix
Q = sim_q_matrix(J, K)

# Simulate subject attributes
subject_alphas = sim_subject_attributes(N, K)

# Simulate Item Data
items_dina = sim_dina_items(subject_alphas, Q, ss, gs)
```

## Authors

Steven Andrew Culpepper and James Joseph Balamuta

## Citing the `dina` package

To ensure future development of the package, please cite `dina`
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("dina")
```

## License

GPL (>= 2)