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llra.datprep<-function(X, mpoints, groups, baseline=NULL){
Xwide <- X
if (ncol(Xwide) %% mpoints > 0)
stop("Number of items must be the same for each timepoint.")
nitems <- dim(Xwide)[2]/mpoints
if(missing(groups)) groups <- rep("CG",dim(Xwide)[1])
covs.prep<-function(groups,baseline){
groups<-as.matrix(groups)
grstr<-apply(groups,1,paste,collapse=":")
grstr <- factor(grstr)
if(!is.null(baseline))
{
basel <- paste(baseline,collapse=":")
grstr <- relevel(grstr,basel)
}
cov.groupvec<-as.numeric(grstr)
names(cov.groupvec)<-grstr
cov.groupvec
}
# sort data according to cov.groupvec
cov.groupvec<-covs.prep(groups,baseline)
Xwide<-Xwide[order(cov.groupvec,decreasing=TRUE),]
cov.groupvec<-sort(cov.groupvec)
# number of people per group
grp_n<-table(cov.groupvec)
names(grp_n)<-unique(names(cov.groupvec))
# convert to long format
Xlong <- matrix(unlist(Xwide), ncol = mpoints)
# assignment vector item x treatment
assign.vec <- as.vector(sapply(1:nitems, function(i)
cov.groupvec + (i-1)*max(cov.groupvec)))
assign.vec <- rev(assign.vec)
assign.vec <- abs(assign.vec-max(assign.vec))+1
names(assign.vec)<-rev(rep(names(cov.groupvec),nitems))
list(X=Xlong, assign.vec=assign.vec, grp_n=grp_n, nitems=nitems)
}
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