Nothing
`sens.spec` <-
structure(function(x,y, risk=1, dir="LESS", plot=F) {
frame <- data.frame(x,y)
var.min <- min(na.omit(x)) # welches ist der niedrigste Wert?
var.max <- max(na.omit(x)) # welches ist der hoechste Wert?
dummy <- var.min
cat("\r")
cat(c("Minimum of value: ", var.min, "\r"))
cat(c("Maximum of value: ", var.max, "\r", "\r"))
cat(c("Risk is coded with: ", risk, "\r"))
if (dir=="GREATER"|dir=="G"|dir=="greater"|dir=="g") {
cat("greater value means higher risk", "\r", "\r")
}
if (dir=="LESS"|dir=="L"|dir=="less"|dir=="l") {
cat("lesser value means higher risk", "\r", "\r")
}
sesp.table <- cbind(999, 999, 999, 999, 999, 999, 999) # dient der Indizierung, wird spaeter geloescht (s.u.)
while(dummy <= var.max) {
### true/false positive/negative
if (dir=="LESS"|dir=="L"|dir=="less"|dir=="l") {
tp <- length(frame$x[frame$x<=dummy & frame$y==risk]) # true positive
fp <- length(frame$x[frame$x<=dummy & frame$y!=risk]) # false positive
tn <- length(frame$x[frame$x>dummy & frame$y!=risk]) # true negative
fn <- length(frame$x[frame$x>dummy & frame$y==risk]) # false negative
}
if (dir=="GREATER"|dir=="G"|dir=="greater"|dir=="g") {
tp <- length(frame$x[frame$x>=dummy & frame$y==risk]) # true positive
fp <- length(frame$x[frame$x>=dummy & frame$y!=risk]) # false positive
tn <- length(frame$x[frame$x<dummy & frame$y!=risk]) # true negative
fn <- length(frame$x[frame$x<dummy & frame$y==risk]) # false negative
}
sensi <- round((tp / (tp+fn)),digits=3) # Sensitivitaet
speci <- round((tn / (tn+fp)),digits=3) # Spezifitaet
sesp.table <- rbind(sesp.table, c(dummy, sensi, speci, tp,fp,tn,fn))
dummy <- (dummy+1)
}
colnames(sesp.table) <- c("Value", "Sensitivy", "Specificy", "tp", "fp", "tn", "fn")
sesp.table <- sesp.table[-1,] # hier werden die "999" geloescht
if (plot==T) {
plot.table <- cbind(sesp.table[,2], sesp.table[,3])
plot(plot.table)
}
if (plot==F) {
print(sesp.table)
cat("\r")
cat("Cut-Off-Points include positive cases", "\r")
cat("\r")
}
}
, comment = "Funktion zur Berechnung von Sensitivitaet und Spezifitaet")
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