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utils.R
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utils.R
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# helper functions
# packages
if (!require("pacman")) install.packages("pacman"); library(pacman)
p_load(dplyr)
# categorical scoring ----
# subdiagnosis items
paranoid_items <- as.character(c(1, 13, 25, 37, 49, 61, 73))
schizoid_items <- as.character(c(2, 14, 26, 38, 50, 62, 74))
schizotypisch_items <- as.character(c(3, 15, 27, 39, 50, 51, 63, 75, 85))
vermeidend_items <- as.character(c(8, 20, 32, 44, 56, 68, 80))
dependent_items <- as.character(c(9, 21, 33, 45, 57, 69, 81, 90))
zwanghaft_items <- as.character(c(10, 22, 34, 46, 58, 70, 82, 91))
antisozial_items <- as.character(c(4, 16, 28, 40, 52, 64, 76, 86))
borderline_items <- as.character(c(5, 17, 29, 41, 53, 65, 77, 87, 92, 94))
histrionisch_items <- as.character(c(6, 18, 30, 42, 54, 66, 78, 88))
narzisstisch_items <- as.character(c(7, 19,31, 43, 55, 67, 79, 89, 93))
nnb_depressiv_items <- as.character(c(11, 23, 35, 47, 59, 71, 83))
nnb_passiv_items <- as.character(c(12, 24, 36, 48, 60, 72, 84))
score_kat_diag <- function(antworten, alg) {
if (alg == "t4_d1") {
antworten <- antworten %>%
mutate(erfuellt = ifelse(Trait > 4 & Distress > 1, 1, 0))
} else if (alg == "t5_d1") {
antworten <- antworten %>%
mutate(erfuellt = ifelse(Trait > 5 & Distress > 1, 1, 0))
}
paranoid <- antworten %>% filter(Item %in% paranoid_items)
schizoid <- antworten %>% filter(Item %in% schizoid_items)
schizotypisch <- antworten %>% filter(Item %in% schizotypisch_items)
vermeidend <- antworten %>% filter(Item %in% vermeidend_items)
dependent <- antworten %>% filter(Item %in% dependent_items)
zwanghaft <- antworten %>% filter(Item %in% zwanghaft_items)
antisozial <- antworten %>% filter(Item %in% antisozial_items)
borderline <- antworten %>% filter(Item %in% borderline_items)
histrionisch <- antworten %>% filter(Item %in% histrionisch_items)
narzisstisch <- antworten %>% filter(Item %in% narzisstisch_items)
nnb_depressiv <- antworten %>% filter(Item %in% nnb_depressiv_items)
nnb_passiv <- antworten %>% filter(Item %in% nnb_passiv_items)
# borderline exception: one of two items is enough --> don't count twice
if (borderline$erfuellt[5] == 1 & borderline$erfuellt[6] == 1) {
borderline$erfuellt[5] == 0
}
diag_paranoid <- ifelse(sum(paranoid$erfuellt) > 3, "ja", "nein")
diag_schizoid <- ifelse(sum(schizoid$erfuellt) > 3, "ja", "nein")
diag_schizotypisch <- ifelse(sum(schizotypisch$erfuellt) > 4, "ja", "nein")
diag_vermeidend <- ifelse(sum(vermeidend$erfuellt) > 3, "ja", "nein")
diag_dependent <- ifelse(sum(dependent$erfuellt) > 4, "ja", "nein")
diag_zwanghaft <- ifelse(sum(zwanghaft$erfuellt) > 3, "ja", "nein")
diag_antisozial <- ifelse(sum(antisozial$erfuellt) > 2, "ja", "nein")
diag_borderline <- ifelse(sum(borderline$erfuellt) > 4, "ja", "nein")
diag_histrionisch <- ifelse(sum(histrionisch$erfuellt) > 4, "ja", "nein")
diag_narzisstisch <- ifelse(sum(narzisstisch$erfuellt) > 4, "ja", "nein")
diag_nnb_depressiv <- ifelse(sum(nnb_depressiv$erfuellt) > 4, "ja", "nein")
diag_nnb_passiv <- ifelse(sum(nnb_passiv$erfuellt) > 3, "ja", "nein")
output <- data.frame(
Diagnose = c("Paranoid",
"Schizoid",
"Schizotypisch",
"Vermeidend-Selbstunsicher",
"Dependent",
"Zwanghaft",
"Antisozial",
"Borderline",
"Histrionisch",
"Narzisstisch",
"NNB-Depressiv",
"NNB-Passiv-Aggressiv"),
`Cut-Off` = c("> 3",
"> 3",
"> 4",
"> 3",
"> 4",
"> 3",
"> 2",
"> 4",
"> 4",
"> 4",
"> 4",
"> 3"),
`Anzahl erfuellter Kriterien` = c(as.integer(sum(paranoid$erfuellt)),
as.integer(sum(schizoid$erfuellt)),
as.integer(sum(schizotypisch$erfuellt)),
as.integer(sum(vermeidend$erfuellt)),
as.integer(sum(dependent$erfuellt)),
as.integer(sum(zwanghaft$erfuellt)),
as.integer(sum(antisozial$erfuellt)),
as.integer(sum(borderline$erfuellt)),
as.integer(sum(histrionisch$erfuellt)),
as.integer(sum(narzisstisch$erfuellt)),
as.integer(sum(nnb_depressiv$erfuellt)),
as.integer(sum(nnb_passiv$erfuellt))),
`erfuellte Kriterien/Items` = c(paste(paranoid$Item[paranoid$erfuellt == 1], collapse = ", "),
paste(schizoid$Item[schizoid$erfuellt == 1], collapse = ", "),
paste(schizotypisch$Item[schizotypisch$erfuellt == 1], collapse = ", "),
paste(vermeidend$Item[vermeidend$erfuellt == 1], collapse = ", "),
paste(dependent$Item[dependent$erfuellt == 1], collapse = ", "),
paste(zwanghaft$Item[zwanghaft$erfuellt == 1], collapse = ", "),
paste(antisozial$Item[antisozial$erfuellt == 1], collapse = ", "),
paste(borderline$Item[borderline$erfuellt == 1], collapse = ", "),
paste(histrionisch$Item[histrionisch$erfuellt == 1], collapse = ", "),
paste(narzisstisch$Item[narzisstisch$erfuellt == 1], collapse = ", "),
paste(nnb_depressiv$Item[nnb_depressiv$erfuellt == 1], collapse = ", "),
paste(nnb_passiv$Item[nnb_passiv$erfuellt == 1], collapse = ", ")),
`Diagnose erfuellt?` = c(diag_paranoid,
diag_schizoid,
diag_schizotypisch,
diag_vermeidend,
diag_dependent,
diag_zwanghaft,
diag_antisozial,
diag_borderline,
diag_histrionisch,
diag_narzisstisch,
diag_nnb_depressiv,
diag_nnb_passiv),
check.names = F
)
return(output)
}
# dimensional scoring ----
# subdiagnosis items
par_items <- as.character(c(1, 13, 25, 37, 49, 61, 73))
sz_items <- as.character(c(2, 14, 26, 38, 50, 62, 74))
st_items <- as.character(c(3, 15, 27, 39, 50, 51, 63, 75, 85))
ver_items <- as.character(c(8, 20, 32, 44, 56, 68, 80))
dep_items <- as.character(c(9, 21, 33, 45, 57, 69, 81, 90))
zwa_items <- as.character(c(10, 22, 34, 46, 58, 70, 82, 91))
as_items <- as.character(c(4, 16, 28, 40, 52, 64, 76, 86))
bdl_items <- as.character(c(5, 17, 29, 41, 53, 65, 77, 87, 92, 94))
his_items <- as.character(c(6, 18, 30, 42, 54, 66, 78, 88))
nar_items <- as.character(c(7, 19,31, 43, 55, 67, 79, 89, 93))
nnb_d_items <- as.character(c(11, 23, 35, 47, 59, 71, 83))
nnb_p_items <- as.character(c(12, 24, 36, 48, 60, 72, 84))
score_dim_diag <- function(antworten) {
par <- antworten %>% filter(Item %in% par_items)
sz <- antworten %>% filter(Item %in% sz_items)
st <- antworten %>% filter(Item %in% st_items)
ver <- antworten %>% filter(Item %in% ver_items)
dep <- antworten %>% filter(Item %in% dep_items)
zwa <- antworten %>% filter(Item %in% zwa_items)
as <- antworten %>% filter(Item %in% as_items)
bdl <- antworten %>% filter(Item %in% bdl_items)
his <- antworten %>% filter(Item %in% his_items)
nar <- antworten %>% filter(Item %in% nar_items)
nnb_d <- antworten %>% filter(Item %in% nnb_d_items)
nnb_p <- antworten %>% filter(Item %in% nnb_p_items)
cluster_a <- data.frame(
Diagnose = c("PAR",
"SZ",
"ST",
"Gesamt"),
Score = c(as.integer(sum(par$Trait)),
as.integer(sum(sz$Trait)),
as.integer(sum(st$Trait)),
as.integer(sum(sum(par$Trait), sum(sz$Trait), sum(st$Trait)))),
check.names = F
)
cluster_b <- data.frame(
Diagnose = c("AS",
"BDL",
"HIS",
"NAR",
"Gesamt"),
Score = c(as.integer(sum(as$Trait)),
as.integer(sum(bdl$Trait)),
as.integer(sum(his$Trait)),
as.integer(sum(nar$Trait)),
as.integer(sum(sum(as$Trait), sum(bdl$Trait), sum(his$Trait), sum(nar$Trait)))),
check.names = F
)
cluster_c <- data.frame(
Diagnose = c("VER",
"DEP",
"ZWA",
"Gesamt"),
Score = c(as.integer(sum(ver$Trait)),
as.integer(sum(dep$Trait)),
as.integer(sum(zwa$Trait)),
as.integer(sum(sum(ver$Trait), sum(dep$Trait), sum(zwa$Trait)))),
check.names = F
)
gesamt <- data.frame(
Cluster = c("A",
"B",
"C",
"Gesamt"),
Score = c(cluster_a$Score[cluster_a$Diagnose == "Gesamt"],
cluster_b$Score[cluster_b$Diagnose == "Gesamt"],
cluster_c$Score[cluster_c$Diagnose == "Gesamt"],
as.integer(sum(cluster_a$Score[cluster_a$Diagnose == "Gesamt"],
cluster_b$Score[cluster_b$Diagnose == "Gesamt"],
cluster_c$Score[cluster_c$Diagnose == "Gesamt"]))),
check.names = F
)
nnb <- data.frame(
Diagnose = c("Depressiv",
"Passiv-Aggressiv"),
Score = c(as.integer(sum(nnb_d$Trait)),
as.integer(sum(nnb_p$Trait))),
check.names = F
)
results_list <- list(cluster_a, cluster_b, cluster_c, gesamt, nnb)
return(results_list)
}