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gscaLCA

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

v0.0.5 · Jun 8, 2020 · GPL-3

Description

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.

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CRAN Check Status

14 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies gridExtra ggplot2 stringr progress psych fastDummies fclust MASS devtools foreach doSNOW nnet gscaLCA

Version History

new 0.0.5 Mar 10, 2026
updated 0.0.5 ← 0.0.3 diff Jun 7, 2020
updated 0.0.3 ← 0.0.2 diff May 24, 2020
new 0.0.2 Oct 8, 2019