CRAN/E | gscaLCA

gscaLCA

Generalized Structure Component Analysis- Latent Class Analysis & Latent Class Regression

Installation

About

Execute Latent Class Analysis (LCA) and Latent Class Regression (LCR) by using Generalized Structured Component Analysis (GSCA). This is explained in Ryoo, Park, and Kim (2019) 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 provides graphs of item response probabilities. In addition, the package enables to estimate the relationship between the prevalence and covariates.

github.com/hee6904/gscaLCA

Key Metrics

Version 0.0.5
R ≥ 2.10
Published 2020-06-08 1412 days ago
Needs compilation? no
License GPL-3
CRAN checks gscaLCA results

Downloads

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Maintainer

Maintainer

Seohee Park

hee6904@gmail.com

Authors

Jihoon Ryoo

aut

Seohee Park

aut / cre

Seoungeun Kim

aut

heungsun Hwaung

aut

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

gscaLCA archive

Depends

R ≥ 2.10

Imports

gridExtra
ggplot2
stringr
progress
psych
fastDummies
fclust
MASS
devtools
foreach
doSNOW
nnet

Suggests

knitr
rmarkdown