https://github.com/tmsalab/slcm

Perform a Bayesian estimation of the exploratory Sparse Latent Class Model for Binary Data described by Chen, Y., Culpepper, S. A., and Liang, F. (2020) <https://doi.org/10.1007/s11336-019-09693-2>
https://github.com/tmsalab/slcm

latent-class-model psychometrics r-package rcpparmadillo sparse

Last synced: 24 days ago
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Perform a Bayesian estimation of the exploratory Sparse Latent Class Model for Binary Data described by Chen, Y., Culpepper, S. A., and Liang, F. (2020) <https://doi.org/10.1007/s11336-019-09693-2>

• Host: GitHub
• URL: https://github.com/tmsalab/slcm
• Owner: tmsalab
• Created: 2023-07-18T04:44:29.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-06-14T01:06:35.000Z (7 months ago)
• Last Synced: 2024-06-14T22:26:51.544Z (7 months ago)
• Topics: latent-class-model, psychometrics, r-package, rcpparmadillo, sparse
• Language: C++
• Homepage: https://tmsalab.github.io/slcm/
• Size: 414 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# slcm

[![R-CMD-check](https://github.com/tmsalab/slcm/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/tmsalab/slcm/actions/workflows/R-CMD-check.yaml)

[![Package-License](http://img.shields.io/badge/license-GPL%20(%3E=2)-brightgreen.svg?style=flat)](http://www.gnu.org/licenses/gpl-2.0.html)

The goal of `slcm` is to provide an implementation of the exploratory

Sparse Latent Class Model (SLCM) for Binary Data described by Chen, Y.,

Culpepper, S. A., and Liang, F. (2020) .

This package contains a new implementation of the proposed SLCM based on

the paper. You may find original papers implementation in the [`inst/`

folder](https://github.com/tmsalab/slcm/tree/main/inst) of the package.

## Installation

You can install the released version of slcm from

[CRAN](https://CRAN.R-project.org) with:

``` r

install.packages("slcm")

```

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

[GitHub](https://github.com/) using:

``` r

# install.packages("devtools")

devtools::install_github("tmsalab/slcm")

```

## Usage

To use `slcm`, load the package using:

``` r

library("slcm")

```

From here, the SLCM model can be estimated using:

``` r

model_slcm = slcm::slcm(

  y = ,

  k = 

)

```

## Authors

James Joseph Balamuta and Steven Andrew Culpepper

## Citing the `slcm` package

To ensure future development of the package, please cite `slcm` package

if used during an analysis or simulation study. Citation information for

the package may be acquired by using in *R*:

``` r

citation("slcm")

```

## License

GPL (\>= 2)