simulate: Simulate

In randomLCA: Random Effects Latent Class Analysis

Simulate

Description

Simulate data from a fitted randomLCA model

Usage

## S3 method for class 'randomLCA'
simulate(object, nsim, seed, ...)

Arguments

object	randomLCA object
nsim	number of data sets to be simulated
seed	random seed
...	additional optional arguments.

Details

Generates random data from the supplied object.

Value

A simulated data frame or a list of simulated data frames.

Author(s)

Ken Beath

Examples

myocardial.lca1 <- randomLCA(myocardial[, 1:4], freq = myocardial$freq, nclass = 1, cores = 1)
myocardial.lca2 <- randomLCA(myocardial[, 1:4], freq = myocardial$freq, cores = 1)
# calculate observed lrt
obslrt <- 2*(logLik(myocardial.lca2)-logLik(myocardial.lca1))

print(obslrt)

nsims <- 999
# generate the simulations
thesims <- simulate(myocardial.lca1, nsims)
# for each simulation determin lrt
simlrt <- rep(NA, nsims)
for (isim in 1:nsims) {
  submodel <- refit(myocardial.lca1, newpatterns = thesims[[isim]])
  fullmodel <- refit(myocardial.lca2, newpatterns = thesims[[isim]])
  simlrt[isim] <- 2*(logLik(fullmodel)-logLik(submodel))
  print(c(isim, simlrt[isim]))
}
# calculate p value as proportion of simulated lrt greater than observed, 
# corrected by adding one to numerator and denominator
print((sum(simlrt >= obslrt)+1)/(nsims+1))

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