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randomLCA (version 1.1-4)

Random Effects Latent Class Analysis

Description

Fits standard and random effects latent class models. The single level random effects model is described in Qu et al and the two level random effects model in Beath and Heller . Examples are given for their use in diagnostic testing.

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Version

Install

install.packages('randomLCA')

Monthly Downloads

897

Version

1.1-4

License

GPL (>= 2)

Maintainer

Ken Beath

Last Published

September 23rd, 2024

Functions in randomLCA (1.1-4)

BIC

BIC for randomLCA object
AIC3

AIC with 3 penalty for randomLCA object
calcCond2Prob

Calculate Conditional Outcome Probabilities for 2 Level Models
maxPostClass

Determines class with maximum posterior class probability for each observation
pap

Positive Action program implementation
plot

Plot a randomLCA object
dentistry

Dental X-ray data
randomLCA

Fits a Latent Class Model including a Random Effect
outcomeProbs

Extract outcome probabilities for randomLCA object
ranef

Extract random effects from a randomLCA object
postClassProbs

Determines posterior class probabilities for fitted model
myocardial

Myocardial Infarction (MI)
hivtests

HIV testing data
refit

Refit an randomLCA object
symptoms

Symptoms data
uterinecarcinoma

Uterine Carcinoma Data
logLik

log Likelikelihood for randomLCA object
summary.randomLCA

Summary for randomLCA object
simulate

Simulate
fitted

fitted values
AIC

AIC for randomLCA object
genderrole

Gender Role Opinion Items
print.randomLCA

print for randomLCA object
calcMargProb

Calculates Marginal Outcome Probabilities
classProbs

Determines class probabilities for fitted model
calcCondProb

Calculate Conditional Outcome Probabilities