ctGenerate
This function generates data according to the specified ctsem model object.
ctGenerate( ctmodelobj, n.subjects = 100, burnin = 0, dtmean = 1, logdtsd = 0, dtmat = NA, wide = FALSE )
ctmodelobj |
ctsem model object from |
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? |
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.
#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)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.