ctGenerate: ctGenerate

In cdriveraus/ctsem: Continuous Time Structural Equation Modelling

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 = 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.
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),
 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)

cdriveraus/ctsem documentation built on April 18, 2024, 5:24 a.m.