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:	1.0.0
Depends:	R (≥ 2.10)
Imports:	DiagrammeR, magrittr, MASS, Rcpp, stats
LinkingTo:	Rcpp
Published:	2024-04-22
DOI:	10.32614/CRAN.package.slca
Author:	Youngsun Kim [aut, cre], Hwan Chung [aut]
Maintainer:	Youngsun Kim <yskstat at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	yes
CRAN checks:	slca results

Documentation:

Reference manual:

slca.pdf

Downloads:

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

Linking:

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