#' @export
create.data.full <- function(raw.results.file,skipped.id.file) {
## read files
input_cdd.data <- read.csv(raw.results.file)
cdd.inds <- read.csv(skipped.id.file, header=F)
cdd.inds <- unique(cdd.inds)
# Create table cdd.data.all
# check if exist column method
if ("method" %in% colnames(input_cdd.data)) {
# remember which rows don't have method cdd (maybe will be needed)
not.cdd.method <- which(input_cdd.data$method != "cdd")
# subset needed data (where method is cdd)
input_cdd.data <- subset(input_cdd.data, method == "cdd")
}
cdd.inds <- rbind(NA,cdd.inds)
#add ID numbers to the input_cdd.data
cdd.data.all <- cbind(cdd.inds,input_cdd.data)
colnames(cdd.data.all)[1] <- "ID"
no.cook.cov <- FALSE
if(all(is.na(cdd.data.all$cook.scores[-1])) || (all(cdd.data.all$cov.ratios[-1]==0))) {
no.cook.cov <- TRUE
}
# check if there are some cov ratios = 0 (it means that covariance step failed for specifick excluded ID)
ID_failed_cov <- c()
if(!all(is.na(cdd.data.all$cook.scores[-1])) && any(cdd.data.all$cov.ratios[-1]==0)) {
ID_failed_cov <- cdd.data.all$ID[(cdd.data.all$cov.ratios==0)]
if(is.na(ID_failed_cov[1])) {
ID_failed_cov <- ID_failed_cov[-1]
}
}
# output
out <- list(input_cdd.data=input_cdd.data,
cdd.data.all=cdd.data.all,
no.cook.cov=no.cook.cov,
ID_failed_cov=ID_failed_cov)
return(out)
}
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