LCAextend: Latent Class Analysis (LCA) with familial dependence in extended pedigrees

This package performs a Latent Class Analysis of phenotypic measurements in pedigrees and a model selection based on one of two methods: likelihood-based cross-validation and Bayesian Information Criterion. It computes also individual and triplet child-parents weights in a pedigree using an upward-downward algorithm. It 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.

AuthorArafat TAYEB <>, Alexandre BUREAU <> and Aurelie Labbe <>
Date of publication2012-03-18 16:07:12
MaintainerAlexandre BUREAU <>

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Man pages

alpha.compute: computes cumulative logistic coefficients using probabilities

attrib.dens: associates to a function of density parameter optimization an...

dens.norm: computes the multinormal density of a given continuous... computes the probability of a given discrete measurement...

downward: performs the downward step of the peeling algorithm and...

downward.connect: performs a downward step for a connector

e.step: performs the E step of the EM algorithm for a single pedigree...

init.norm: computes initial values for the EM algorithm in the case of...

init.ordi: computes the initial values for EM algorithm in the case of...

init.p.trans: initializes the transition probabilities

LCAextend-package: Latent Class Analysis (LCA) and model selection for pedigree...

lca.model: fits latent class models for phenotypic measurements in... selects a latent class model for pedigree data

n.param: computes the number of parameters of a model

optim.const.ordi: performs the M step for the measurement distribution...

optim.diff.norm: performs the M step for measurement density parameters in...

optim.equal.norm: performs the M step for measurement density parameters in...

optim.gene.norm: performs the M step for measurement density parameters in...

optim.indep.norm: performs the M step for measurement density parameters in...

optim.noconst.ordi: performs the M step for the measurement distribution...

optim.probs: performs the M step of the EM algorithm for the probability...

param.cont: parameters to be used for examples in the case of continuous...

param.ordi: parameters to be used for examples in the case of discrete or...

p.compute: computes the probability vector using logistic coefficients

ped.cont: pedigrees with continuous data to be used for examples

ped.ordi: pedigrees with discrete or ordinal data to be used for...

peel: peeling order of pedigrees and couples in pedigrees computes the posterior probability of observations of a child computes the posterior probability of observations of a...

probs: probabilities parameters to be used for examples

upward: performs the upward step of the peeling algorithm of a...

upward.connect: performs the upward step for a connector

weight.famdep: performs the computation of triplet and individual weights...

weight.nuc: performs the computation of unnormalized triplet and...


alpha.compute Man page
attrib.dens Man page
dens.norm Man page Man page
downward Man page
downward.connect Man page
e.step Man page
init.norm Man page
init.ordi Man page
init.p.trans Man page
LCAextend Man page
LCAextend-package Man page
lca.model Man page Man page
n.param Man page
optim.const.ordi Man page
optim.diff.norm Man page
optim.equal.norm Man page
optim.gene.norm Man page
optim.indep.norm Man page
optim.noconst.ordi Man page
optim.probs Man page
param.cont Man page
param.ordi Man page
p.compute Man page
ped.cont Man page
ped.ordi Man page
peel Man page Man page Man page
probs Man page
upward Man page
upward.connect Man page
weight.famdep Man page
weight.nuc Man page


LCAextend/man/weight.nuc.Rd LCAextend/man/weight.famdep.Rd LCAextend/man/upward.connect.Rd LCAextend/man/upward.Rd LCAextend/man/probs.Rd LCAextend/man/peel.Rd LCAextend/man/ped.ordi.Rd LCAextend/man/ped.cont.Rd LCAextend/man/param.ordi.Rd LCAextend/man/param.cont.Rd LCAextend/man/ LCAextend/man/ LCAextend/man/p.compute.Rd LCAextend/man/optim.probs.Rd LCAextend/man/optim.noconst.ordi.Rd LCAextend/man/optim.indep.norm.Rd LCAextend/man/optim.gene.norm.Rd LCAextend/man/optim.equal.norm.Rd LCAextend/man/optim.diff.norm.Rd LCAextend/man/optim.const.ordi.Rd LCAextend/man/n.param.Rd LCAextend/man/ LCAextend/man/lca.model.Rd LCAextend/man/init.p.trans.Rd LCAextend/man/init.ordi.Rd LCAextend/man/init.norm.Rd LCAextend/man/e.step.Rd LCAextend/man/downward.connect.Rd LCAextend/man/downward.Rd LCAextend/man/ LCAextend/man/dens.norm.Rd LCAextend/man/attrib.dens.Rd LCAextend/man/alpha.compute.Rd LCAextend/man/LCAextend-package.Rd
LCAextend/R/weight.nuc.R LCAextend/R/weight.famdep.R LCAextend/R/upward.connect.R LCAextend/R/upward.R LCAextend/R/ LCAextend/R/
LCAextend/R/optim.probs.R LCAextend/R/optim.noconst.ordi.R LCAextend/R/optim.indep.norm.R LCAextend/R/optim.gene.norm.R LCAextend/R/optim.equal.norm.R LCAextend/R/optim.diff.norm.R
LCAextend/R/n.param.R LCAextend/R/
LCAextend/R/init.p.trans.R LCAextend/R/init.ordi.R LCAextend/R/init.norm.R LCAextend/R/e.step.R LCAextend/R/downward.connect.R LCAextend/R/downward.R
LCAextend/R/dens.norm.R LCAextend/R/attrib.dens.R LCAextend/R/alpha.compute.R

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