https://github.com/tmsalab/dina

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

armadillo bayesian gibbs-sampler irt item-response-theory psychometrics rcpp rcpparmadillo

Last synced: 7 days ago
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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>.

• Host: GitHub
• URL: https://github.com/tmsalab/dina
• Owner: tmsalab
• Created: 2017-04-26T01:57:18.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2020-07-31T16:01:59.000Z (over 4 years ago)
• Last Synced: 2024-03-26T10:03:10.040Z (9 months ago)
• Topics: armadillo, bayesian, gibbs-sampler, irt, item-response-theory, psychometrics, rcpp, rcpparmadillo
• Language: C++
• Homepage: https://tmsalab.github.io/dina
• Size: 104 KB
• Stars: 13
• Watchers: 4
• Forks: 5
• Open Issues: 4
• Metadata Files:
  • Readme: README.Rmd

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README

        
---

output: github_document

---

```{r, echo = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "README-"

)

```

# 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) 

.

## 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(, , 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)