Nothing
spaplot <-
function(x, response, grouping=NULL, ylim=NULL, col=NULL, ...){
dat <- x$df
ids <- unique(dat[, 1])
times <- x$times
measure <- rep(0, length(times))
if(is.null(ylim)){
minO <- min(dat[, response])
maxO <- max(dat[, response])
} else {
minO <- ylim[1]
maxO <- ylim[2]
}
plot(times, measure, ylim=c(minO, maxO), type="n", axes=T, ...)
dat.obs <- dat[dat$obs.type==1, ]
if(is.null(grouping)){
if(length(col)==1){col <- c(col, col)}
if(is.null(col)){col <- c("black", "black")}
for(i in 1:length(ids)){
lines(times, dat[dat[, 1]==ids[i], response], lty=2, col=col[2], ...)
lines(dat.obs[dat.obs[, 1]==ids[i], 2],
dat.obs[dat.obs[, 1]==ids[i], response], lty =1, col=col[1], ...)
}
cat(paste("Spaghetti plots created for variable:", response))
cat("\nFull drawn: observed values.")
cat("\nStipulated: hypothetical values.\n")
cat("\n")
} else {
if(is.null(col)){col <- 1:50}
groups <- unique(dat[, grouping])
# Ranking of nr of ids in each group level. For added visibility the biggest
# group. Must match to group as table() rearanges alphanumerically.
obsranking <- sort(rank(table(dat[, grouping]), ties.method="first"),
decreasing=TRUE)
plotseq <- match(names(obsranking), groups)
for(k in obsranking) {
kdat <- dat[dat[, grouping]==groups[k], ]
kdat.obs <- kdat[kdat$obs.type==1, ]
kids <- unique(kdat[, 1])
for(i in 1:length(kids)){
lines(times, kdat[kdat[, 1]==kids[i], response], lty=2, col=col[k], ...)
lines(kdat.obs[kdat.obs[, 1]==kids[i], 2],
kdat.obs[kdat.obs[, 1]==kids[i], response], lty=1, col=col[k], ...)
}
}
cat(paste("Spaghetti plots created for variable:", response))
cat("\nFull drawn: observed values.")
cat("\nStipulated: hypothetical values.\n")
cat(paste("\nResponse variable separated by:"), grouping, "which has",
length(groups), "levels.\n")
cat(paste0( paste("Group:", groups), " has color ",
col[1:length(groups)],"."))
cat("\n")
}
}
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