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

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) . 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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install.packages("gscaLCA")

0.0.5 by Seohee Park, 2 months ago


https://github.com/hee6904/gscaLCA


Browse source code at https://github.com/cran/gscaLCA


Authors: Jihoon Ryoo [aut] , Seohee Park [aut, cre] , Seoungeun Kim [aut] , heungsun Hwaung [aut]


Documentation:   PDF Manual  


GPL-3 license


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

Suggests knitr, rmarkdown


See at CRAN