Hello all. I am trying to run PAN, multilevel
multiple imputation program, in R to impute missing
data in a longitudinal dataset. I could successfully
run the multiple imputation when I only imputed one
variable. However, when I tried to impute a
time-varying covariate as well as a response variable,
I received an error message, �Error: subscript out of
bounds.� Can anyone tell if my commands contain any
mistakes?
First I imported SAS dataset �sim� which includes a
response variable �MIY1�, a time-varying covariate
�TCOV1�, TIME, GROUP (0 or 1), and ID. 200
participants were included and measurement occurred
six times. Approximately 25% of participants dropped
out at end.
> sim <- read.xport('c:\\xptds.dat')
>
> int <- rep(1,1200)
> y <- cbind(sim$MIY1,sim$TCOV1)
> subj <- sim$ID
> pred <- cbind(int, sim$TIME, sim$GROUP)
>
> xcol <- 1:3
> zcol <- 1
> prior <- list(a=2,Binv=4,c=2,Dinv=4)
> result <-
pan(y,subj,pred,xcol,zcol,prior,seed=13579,iter=1000)
Error: subscript out of bounds
By the way, I also received the same error message
when I tried to include intercept and time in Zcol, a
matrix for random effect specification. I used
command � zcol <- 1:2�. Does anybody know if this
error is due to sample size/proportion of missing data
or due to command mistake?
I truly appreciate any feedbacks.
Best regards,
Eishi
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