ctsem (version 3.0.4)

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, wide = TRUE)

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 burnin+Tpoints-1 columns, containing positive numeric values for all time intervals between measurements. If not NA, dtmean and logdtsd are ignored.

wide

Logical. Output in wide format?

Details

TRAITVAR and MANIFESTRAITVAR are treated as Cholesky factor covariances of CINT and MANIFESTMEANS, respectively. 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

# NOT RUN {
#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),
 TRAITVAR=matrix(c(.5,.2,0,.8),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))

data<-ctGenerate(generatingModel,n.subjects=15,burnin=10)
# }