Package: randomLCA 1.1-4

randomLCA: Random Effects Latent Class Analysis

Fits standard and random effects latent class models. The single level random effects model is described in Qu et al <doi:10.2307/2533043> and the two level random effects model in Beath and Heller <doi:10.1177/1471082X0800900302>. Examples are given for their use in diagnostic testing.

Authors:Ken Beath [aut, cre]

randomLCA_1.1-4.tar.gz
randomLCA_1.1-4.zip(r-4.7)randomLCA_1.1-4.zip(r-4.6)randomLCA_1.1-4.zip(r-4.5)
randomLCA_1.1-4.tgz(r-4.6-x86_64)randomLCA_1.1-4.tgz(r-4.6-arm64)randomLCA_1.1-4.tgz(r-4.5-x86_64)randomLCA_1.1-4.tgz(r-4.5-arm64)
randomLCA_1.1-4.tar.gz(r-4.7-arm64)randomLCA_1.1-4.tar.gz(r-4.7-x86_64)randomLCA_1.1-4.tar.gz(r-4.6-arm64)randomLCA_1.1-4.tar.gz(r-4.6-x86_64)
randomLCA_1.1-4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
randomLCA/json (API)

# Install 'randomLCA' in R:

install.packages('randomLCA', repos = c('https://kjbeath.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

dentistry - Dental X-ray data
genderrole - Gender Role Opinion Items
hivtests - HIV testing data
myocardial - Myocardial Infarction
pap - Positive Action program implementation
symptoms - Symptoms data
uterinecarcinoma - Uterine Carcinoma Data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.23 score 56 scripts 616 downloads 3 mentions 16 exports 16 dependencies

Last updated from:10de31e3d5. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	172
linux-devel-x86_64	OK	188
source / vignettes	OK	157
linux-release-arm64	OK	160
linux-release-x86_64	OK	142
macos-release-arm64	OK	94
macos-release-x86_64	OK	183
macos-oldrel-arm64	OK	122
macos-oldrel-x86_64	OK	246
windows-devel	OK	104
windows-release	OK	94
windows-oldrel	OK	98
wasm-release	OK	101

Exports:AIC3 calcCond2Prob calcCondProb calcMargProb classProbs maxPostClass outcomeProbs postClassProbs print.randomLCA randomLCA ranef ranef.randomLCA refit refit.randomLCA simulate.randomLCA summary.randomLCA

Dependencies:boot codetools digest doParallel doRNG fastGHQuad foreach iterators lattice Matrix Rcpp RcppArmadillo RcppParallel Rfast rngtools zigg

randomLCA: An R Package for Latent Class with Random Effects Analysis

Introduction | Models | Examples | Summary

Rendered fromrandomLCA-package.pdf.asisusingR.rsp::asis

Last update: 2017-03-01
Started: 2017-03-01

Citation

Readme and manuals

Help Manual

Help page	Topics
AIC for randomLCA object	AIC.randomLCA
AIC with 3 penalty for randomLCA object	AIC3
BIC for randomLCA object	BIC.randomLCA
Calculate Conditional Outcome Probabilities for 2 Level Models	calcCond2Prob
Calculate Conditional Outcome Probabilities	calcCondProb
Calculates Marginal Outcome Probabilities	calcMargProb
Determines class probabilities for fitted model	classProbs
Dental X-ray data	dentistry
fitted values	fitted.randomLCA
Gender Role Opinion Items	genderrole
HIV testing data	hivtests
log Likelikelihood for randomLCA object	logLik.randomLCA
Determines class with maximum posterior class probability for each observation	maxPostClass maxPostClass.randomLCA
Myocardial Infarction (MI)	myocardial
Extract outcome probabilities for randomLCA object	outcomeProbs outcomeProbs.randomLCA
Positive Action program implementation	pap
Plot a randomLCA object	plot.randomLCA
Determines posterior class probabilities for fitted model	postClassProbs postClassProbs.randomLCA
print for randomLCA object	print.randomLCA
Fits a Latent Class Model including a Random Effect	randomLCA
Extract random effects from a randomLCA object	ranef ranef.randomLCA
Refit an randomLCA object	refit refit.randomLCA
Simulate	simulate.randomLCA
Summary for randomLCA object	summary.randomLCA
Symptoms data	symptoms
Uterine Carcinoma Data	uterinecarcinoma

Package: randomLCA 1.1-4

randomLCA: Random Effects Latent Class Analysis

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)