Latent Class Analysis (LCA) with Familial Dependence in Extended
Pedigrees
Description
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.