ctsem (version 3.11.0)

ctGenerate: ctGenerate

Description

This function generates data according to the specified ctsem model object.

Usage

ctGenerate(
  ctmodelobj,
  n.subjects = 100,
  burnin = 0,
  dtmean = 1,
  logdtsd = 0,
  dtmat = NA,
  Tpoints = NULL,
  wide = FALSE
)

Arguments

ctmodelobj

ctsem model object from ctModel.

n.subjects

Number of subjects to output.

burnin

Number of initial time points to discard (to simulate stationary data)

dtmean

Positive numeric. Average time interval (delta T) to use.

logdtsd

Numeric. Standard deviation for variability of the time interval.

dtmat

Either NA, or numeric matrix of n.subjects rows and Tpoints-1 columns, containing positive numeric values for all time intervals between measurements. If not NA, dtmean and logdtsd are ignored.

Tpoints

Optional number of time points to generate. If supplied, this overrides any Tpoints stored in ctmodelobj. If not supplied, ctGenerate uses ctmodelobj$Tpoints when available.

wide

Logical. Output in wide format?

Details

Covariance related matrices are treated as Cholesky factors. TRAITTDPREDCOV and TIPREDCOV matrices are not accounted for, at present. The first 1:n.TDpred rows and columns of TDPREDVAR are used for generating tdpreds at each time point.

Examples

#generate data for 2 process model, each process measured by noisy indicator, 
#stable individual differences in process levels.

generatingModel<-ctModel(Tpoints=8,n.latent=2,n.TDpred=0,n.TIpred=0,n.manifest=2,
 MANIFESTVAR=diag(.1,2),
 LAMBDA=diag(1,2),
 DRIFT=matrix(c(-.2,-.05,-.1,-.1),nrow=2),
 DIFFUSION=matrix(c(1,.2,0,4),2),
 CINT=matrix(c(1,0),nrow=2),
 T0MEANS=matrix(0,ncol=1,nrow=2),
 T0VAR=diag(1,2))

nsubjects <- 15
traitChol <- matrix(c(.5,.2,0,.8),nrow=2)
subjectCint <- t(replicate(nsubjects, as.numeric(traitChol %*% rnorm(2))))
datalist <- vector("list", nsubjects)
for(i in seq_len(nsubjects)){
  subjectModel <- generatingModel
  subjectModel$CINT <- matrix(subjectCint[i,], ncol = 1)
  d <- ctGenerate(subjectModel,n.subjects=1,burnin=10)
  d[,'id'] <- i
  datalist[[i]] <- d
}
data <- do.call(rbind, datalist)