slca: Structural Modeling for Multiple Latent Class Variables

Provides comprehensive tools for the implementation of Structural Latent Class Models (SLCM), including Latent Transition Analysis (LTA; Linda M. Collins and Stephanie T. Lanza, 2009) <doi:10.1002/9780470567333>, Latent Class Profile Analysis (LCPA; Hwan Chung et al., 2010) <doi:10.1111/j.1467-985x.2010.00674.x>, and Joint Latent Class Analysis (JLCA; Saebom Jeon et al., 2017) <doi:10.1080/10705511.2017.1340844>, and any other extended models involving multiple latent class variables.

Version: 1.2.0
Depends: R (≥ 2.10)
Imports: DiagrammeR, magrittr, MASS, Rcpp, stats
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0)
Published: 2024-11-01
DOI: 10.32614/CRAN.package.slca
Author: Youngsun Kim ORCID iD [aut, cre], Hwan Chung ORCID iD [aut]
Maintainer: Youngsun Kim <yskstat at gmail.com>
BugReports: https://github.com/kim0sun/slca/issues
License: GPL (≥ 3)
URL: https://kim0sun.github.io/slca/
NeedsCompilation: yes
Citation: slca citation info
Materials: README
CRAN checks: slca results

Documentation:

Reference manual: slca.pdf

Downloads:

Package source: slca_1.2.0.tar.gz
Windows binaries: r-devel: slca_1.0.0.zip, r-release: slca_1.2.0.zip, r-oldrel: slca_1.2.0.zip
macOS binaries: r-release (arm64): slca_1.2.0.tgz, r-oldrel (arm64): slca_1.2.0.tgz, r-release (x86_64): slca_1.2.0.tgz, r-oldrel (x86_64): slca_1.2.0.tgz
Old sources: slca archive

Linking:

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