#' get_pgsi function
#' @param dataset original dataset "PGSI" from the bundle
#' @param completers boolean parameter, if True filters out participants that are not labeled as completers
#' @return dataframe with 4 columns:
#' PIN, pgsi_sum, pgsi_cat, pgsi_severity
#' @export
get_pgsi <- function(dataset, subscales=F, completers=T){
if(nrow(dataset) == 0 | ncol(dataset) == 0){
stop("Empty dataset")
}
dataset$PIN <- gsub("'", "", dataset$PIN)
essential_cols <- c("pin", "complete", "item", "response")
colnames(dataset) <- tolower(colnames(dataset))
if(!all(essential_cols %in% colnames(dataset))){
stop(essential_cols[!essential_cols %in% colnames(dataset)]," column(s) not found in the dataset")
}
if(any(is.na(dataset["pin"])) | any(dataset["pin"] == "")){
stop("Missed data in pin column")
}
if(any(is.na(dataset["item"])) | any(dataset["pin"] == "")){
stop("Missed data in item column")
}
if(any(is.na(dataset$response))){
stop("You have NAs in response columns!")
}
if(!all(dataset$response %in% c("Never", "Sometimes","Most of the time", "Almost always"))){
stop("Range constraints are broken!")
}
if(!all(as.character(dataset$item) %in% as.character(c(1:9)) )){
stop("Item constraints are broken!")
}
if(completers){
num_participants <- unique(dataset[dataset$complete == 'y', "pin"])
dataset <- dataset[dataset$complete == "y", ]
if(nrow(dataset) == 0){
stop("There are no completers in your dataset")
}
} else {
num_participants <- unique(dataset$pin)
}
dataset$item <- as.numeric(dataset$item)
dataset$response <- as.character(dataset$response)
dataset$response <- pgsi_scale$score[match(dataset$response, pgsi_scale$response)]
df_sum <- aggregate(response ~ pin, data = dataset, sum, na.action = NULL)
df_sum$pgsi_cat <- ifelse(df_sum$response >= thr_pgsi, 1, 0)
df_sum$pgsi_sev <- ifelse(df_sum$response >= 8, 3,
ifelse((df_sum$response>= 3 & df_sum$response <= 7), 2,
ifelse((df_sum$response >= 1 & df_sum$response <= 2), 1, 0)))
colnames(df_sum) <- c("PIN", "pgsi_sum", "pgsi_cat", "pgsi_sev")
return(df_sum)
}
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