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gscaLCA: 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) <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.
Getting started
Browse package contents
Package details |
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| Author | Jihoon Ryoo [aut], Seohee Park [aut, cre], Seoungeun Kim [aut], heungsun Hwaung [aut] |
| Maintainer | Seohee Park <hee6904@gmail.com> |
| License | GPL-3 |
| Version | 0.0.5 |
| URL | https://github.com/hee6904/gscaLCA |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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