calcCond2Prob: Calculate Conditional Outcome Probabilities for 2 Level...

In randomLCA: Random Effects Latent Class Analysis

Calculate Conditional Outcome Probabilities for 2 Level Models

Description

The conditional probabilities are obtained integrating over the period random effect.

Usage

calcCond2Prob(object, conditionalp = 0.5)

Arguments

object	RandomLCA object
conditionalp	the percentiles for the random effect

Value

Returns a data frame containing class, block, outcome, outcomep (outcome probability) and perc (percentiles of the random effect) if conditionalp is specified. For example a conditionalp of 0.5 is the 50th percentile or the median corresponding to a random effect of zero. 0.025 and 0.975 correspond to the 2.5th and 97.5th percential, so the region between them if 95% of the variation in the data.

Author(s)

Ken Beath [e-mail]

Examples

symptoms.lca2random2 <- randomLCA(symptoms[, 1:16], freq = symptoms$Freq, 
	random = TRUE, level2 = TRUE, nclass = 2, level2size = 4, constload = FALSE, cores = 1)
print(calcCond2Prob(symptoms.lca2random2))

randomLCA documentation built on July 9, 2023, 6:09 p.m.