gscaLCA: Generalized Structure Component Analysis- Latent Class Analysis

Execute Latent Class Analysis (LCA) by using Generalized Structured Component Analysis (GSCA). This is explained in Ryoo, Park, and Kim (2009) <doi:10.1007/s41237-019-00084-6>. It estimates the parameters of latent class prevalence and item response probability in LCA with a single line comment. It also provide graphs of item response probabilities.

Version: 0.0.2
Depends: R (≥ 2.10)
Imports: gridExtra, ggplot2, stringr, progress, psych, fastDummies, fclust, MASS, devtools, foreach, doSNOW
Suggests: knitr, rmarkdown, R.rsp
Published: 2019-10-09
Author: Jihoon Ryoo [aut], Seohee Park [aut, cre], Seoungeun Kim [aut], heungsun Hwaung [aut]
Maintainer: Seohee Park <hee6904 at gmail.com>
License: GPL-3
URL: https://github.com/hee6904/gscaLCA
NeedsCompilation: no
Materials: README
CRAN checks: gscaLCA results

Downloads:

Reference manual: gscaLCA.pdf
Package source: gscaLCA_0.0.2.tar.gz
Windows binaries: r-devel: gscaLCA_0.0.2.zip, r-release: gscaLCA_0.0.2.zip, r-oldrel: gscaLCA_0.0.2.zip
OS X binaries: r-release: gscaLCA_0.0.2.tgz, r-oldrel: gscaLCA_0.0.2.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=gscaLCA to link to this page.