Nothing
`datprep_LLTM` <-
function(X,W,mpoints,Groups,sum0)
{
# Design matrix see Fischer & Molenaar, p. 159
#TFrow <- (rowSums(X)==0 | rowSums(X)==(dim(X)[2])) #el. persons with 0/K rawscore
#X <- X[!TFrow,]
ngroups <- max(Groups)
X01 <- X
N <- dim(X)[1] #number of persons
K <- dim(X)[2]/mpoints #number of items
mt_vek <- rep(1,K)
#automatized generation of the design matrix W
if (length(W)==1) {
W11diag <- diag(1,(sum(mt_vek)-1)) #build up design matrix
if (sum0) {
w110 <- rep(-1,(sum(mt_vek)-1)) #sum0 restriction
} else {
w110 <- rep(0,(sum(mt_vek)-1)) #first item category parameter set to 0
}
W11 <- rbind(w110,W11diag) #RM design matrix
ZW <- dim(W11)[1]
W1 <- NULL
for (i in 1:(mpoints*ngroups)) W1 <- rbind(W1,W11) #first part with virtual items
if (mpoints > 1) { #more than 1 measurement points
if (ngroups > 1) { #more than 1 group/more mpoints
t_mp1 <- rep(1:mpoints,rep(ZW*ngroups,mpoints))
t_mp <- factor(t_mp1)
g_ng1 <- rep(rep(1:ngroups,rep(ZW,ngroups)),mpoints)
g_ng <- factor(g_ng1)
W2 <- model.matrix(~t_mp+g_ng)[,-1] #main effects g and mp
W2[1:(ZW*ngroups),] <- 0 #remove main effects for the first test occasion
} else { #1 group/more mpoints
t_mp <- gl(mpoints,ZW) #factor for measurement points
W2 <- model.matrix(~t_mp)[,-1] }
} else if (ngroups > 1) { #1 mpoint/more groups
g_ng <- gl(ngroups,ZW)
W2 <- model.matrix(~g_ng)[,-1]
warning("Group contrasts without repeated measures can not be estimated!")
} else if (ngroups == 1) W2 <- NULL #1 mpoint/1 group
W <- cbind(W1,W2)
colnames(W) <- NULL
rownames(W) <- NULL
}
list(X=X,X01=X01,mt_vek=mt_vek,W=W)
#Output: X01 ... 0/1 response matrix of dimension N*rtot
# mt_vek ... vector of length K with number of categories - 1 (for each item)
# W ... design matrix of dimension (K*T)*((K-1)*(T-1)+1)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.