LCAextend: Latent Class Analysis (LCA) with Familial Dependence in Extended Pedigrees

Latent Class Analysis of phenotypic measurements in pedigrees and model selection based on one of two methods: likelihood-based cross-validation and Bayesian Information Criterion. Computation of individual and triplet child-parents weights in a pedigree is performed using an upward-downward algorithm. The model takes into account the familial dependence defined by the pedigree structure by considering that a class of a child depends on his parents classes via triplet-transition probabilities of the classes. The package handles the case where measurements are available on all subjects and the case where measurements are available only on symptomatic (i.e. affected) subjects. Distributions for discrete (or ordinal) and continuous data are currently implemented. The package can deal with missing data.

Version: 1.3
Depends: R (≥ 2.1.0)
Imports: boot, mvtnorm, rms, kinship2
Published: 2018-07-07
DOI: 10.32614/CRAN.package.LCAextend
Author: Arafat TAYEB, Alexandre BUREAU and Aurelie Labbe
Maintainer: Alexandre BUREAU <alexandre.bureau at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: LCAextend results


Reference manual: LCAextend.pdf


Package source: LCAextend_1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): LCAextend_1.3.tgz, r-oldrel (arm64): LCAextend_1.3.tgz, r-release (x86_64): LCAextend_1.3.tgz, r-oldrel (x86_64): LCAextend_1.3.tgz
Old sources: LCAextend archive


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