iauc.comp {survcomp} | R Documentation |
This function compares two integrated areas under the curves (IAUC) through the results of time-dependent ROC curves at some points in time. The statistical test is a Wilcoxon rank sum test for dependent samples.
iauc.comp(auc1, auc2, time)
auc1 |
vector of AUCs computed from the first time-dependent ROC curves for some points in time |
auc2 |
vector of AUCs computed from the second time-dependent ROC curves for some points in time |
time |
vector of points in time for which the AUCs are computed |
The two vectors of AUCs must be computed from the same samples (and corresponding survival data) and for the same points in time. The function uses a Wilcoxon rank sum test for dependent samples.
p.value |
p-value from the Wilcoxon rank sum test for the comparison iauc1 > iauc2 |
iauc1 |
value of the IAUC for the first set of time-depdent ROC curves |
iauc2 |
value of the IAUC for the second set of time-depdent ROC curves |
Benjamin Haibe-Kains
Wilcoxon, F. (1945) "Individual comparisons by ranking methods", Biometrics Bulletin, 1, pages 80–83.
Haibe-Kains, B. and Desmedt, C. and Sotiriou, C. and Bontempi, G. (2008) "A comparative study of survival models for breast cancer prognostication based on microarray data: does a single gene beat them all?", Bioinformatics, 24, 19, pages 2200–2208.
set.seed(12345) age <- rnorm(30, 50, 10) size <- rexp(30,1) stime <- rexp(30) cens <- runif(30,.5,2) sevent <- as.numeric(stime <= cens) stime <- pmin(stime, cens) ##time-dependent ROC curves tt <- unique(sort(stime[sevent == 1])) ##size mytdroc1 <- NULL for(i in 1:length(tt)) { rr <- tdrocc(x=size, surv.time=stime, surv.event=sevent, time=tt[i], na.rm=TRUE, verbose=FALSE) mytdroc1 <- c(mytdroc1, list(rr)) } auc1 <- unlist(lapply(mytdroc1, function(x) { return(x$AUC) })) ##age mytdroc2 <- NULL for(i in 1:length(tt)) { rr <- tdrocc(x=age, surv.time=stime, surv.event=sevent, time=tt[i], na.rm=TRUE, verbose=FALSE) mytdroc2 <- c(mytdroc2, list(rr)) } auc2 <- unlist(lapply(mytdroc2, function(x) { return(x$AUC) })) iauc.comp(auc1=auc1, auc2=auc2, time=tt)