drizopoulos
commented
2 years ago Check JMbayes2
—— Dimitris Rizopoulos Professor of Biostatistics Erasmus University Medical Center The Netherlands
From: ChenXinaha @.> Sent: Sunday, April 24, 2022 11:11:15 AM To: drizopoulos/JMbayes @.> Cc: Subscribed @.***> Subject: [drizopoulos/JMbayes] Bugs in the function aucJM (Issue #91)
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Hello, I think there may be some problems in the function aucJM， in the follow code,because " if (any(dupl <- duplicated(Time))) { Time[dupl] <- Time[dupl] + runif(length(Time[dupl]), 1e-07, 1e-06) }" only keep the unique event time, which will result in removing subjects whose raw event time less than "Thoriz" using "Ti <= Thoriz" and errors in the estimation of auc. Further, I don't understand the effect of "Time[dupl] <- Time[dupl] + runif(length(Time[dupl]), 1e-07, 1e-06)".
I hope you can answer that for me, thanks very much !
names(Time) <- names(event) <- as.character(unique(id))
if (any(dupl <- duplicated(Time))) {
Time[dupl] <- Time[dupl] + runif(length(Time[dupl]), 1e-07, 1e-06)}
if (!all(names(pi.u.t) == names(Time)))
stop("mismatch between 'Time' variable names and survival probabilities names.")auc <- if (length(Time) > 1) {
pairs <- combn(as.character(unique(id)), 2)
Ti <- Time[pairs[1, ]]
Tj <- Time[pairs[2, ]]
di <- event[pairs[1, ]]
dj <- event[pairs[2, ]]
pi.u.t.i <- pi.u.t[pairs[1, ]]
pi.u.t.j <- pi.u.t[pairs[2, ]]
ind1 <- (Ti <= Thoriz & (di == 1 | di == 3)) & Tj > Thoriz
ind2 <- (Ti <= Thoriz & (di == 0 | di == 2)) & Tj > Thoriz
ind3 <- (Ti <= Thoriz & (di == 1 | di == 3)) & (Tj <= Thoriz & (dj == 0 | dj == 2))
ind4 <- (Ti <= Thoriz & (di == 0 | di == 2)) & (Tj <= Thoriz & (dj == 0 | dj == 2))
names(ind1) <- names(ind2) <- names(ind3) <- names(ind4) <- paste(names(Ti), names(Tj), sep = "_")
ind <- ind1 | ind2 | ind3 | ind4
if (any(ind2)) {
nams <- strsplit(names(ind2[ind2]), "_")
nams_i <- sapply(nams, "[", 1)
unq_nams_i <- unique(nams_i)
pi2 <- if (is_counting) {
survfitJM(object, newdata = newdata2[id %in% unq_nams_i, ], idVar = idVar,
last.time = Time[unq_nams_i], survTimes = Thoriz,
M = M, LeftTrunc_var = all.vars(TermsT)[1L])
} else {
survfitJM(object, newdata = newdata2[id %in% unq_nams_i, ], idVar = idVar,
last.time = Time[unq_nams_i], survTimes = Thoriz, M = M)
}
pi2 <- 1 - sapply(pi2$summaries, "[", 1, 2)
ind[ind2] <- ind[ind2] * pi2[nams_i]
}
if (any(ind3)) {
nams <- strsplit(names(ind3[ind3]), "_")
nams_j <- sapply(nams, "[", 2)
unq_nams_j <- unique(nams_j)
pi3 <- if (is_counting) {
survfitJM(object, newdata = newdata2[id %in% unq_nams_j, ], idVar = idVar,
last.time = Time[unq_nams_j], survTimes = Thoriz,
M = M, LeftTrunc_var = all.vars(TermsT)[1L])
} else {
survfitJM(object, newdata = newdata2[id %in% unq_nams_j, ], idVar = idVar,
last.time = Time[unq_nams_j], survTimes = Thoriz, M = M)
}
pi3 <- sapply(pi3$summaries, "[", 1, 2)
ind[ind3] <- ind[ind3] * pi3[nams_j]
}
if (any(ind4)) {
nams <- strsplit(names(ind4[ind4]), "_")
nams_i <- sapply(nams, "[", 1)
nams_j <- sapply(nams, "[", 2)
unq_nams_i <- unique(nams_i)
unq_nams_j <- unique(nams_j)
if (is_counting) {
pi4_i <- survfitJM(object, newdata = newdata2[id %in% unq_nams_i, ],
idVar = idVar, last.time = Time[unq_nams_i], survTimes = Thoriz,
M = M,
LeftTrunc_var = all.vars(TermsT)[1L])
pi4_j <- survfitJM(object, newdata = newdata2[id %in% unq_nams_j, ],
idVar = idVar, last.time = Time[unq_nams_j], survTimes = Thoriz,
M = M,
LeftTrunc_var = all.vars(TermsT)[1L])
} else {
pi4_i <- survfitJM(object, newdata = newdata2[id %in% unq_nams_i, ],
idVar = idVar, last.time = Time[unq_nams_i], survTimes = Thoriz,
M = M)
pi4_j <- survfitJM(object, newdata = newdata2[id %in% unq_nams_j, ],
idVar = idVar, last.time = Time[unq_nams_j], survTimes = Thoriz,
M = M)
}
pi4_i <- 1 - sapply(pi4_i$summaries, "[", 1, 2)
pi4_j <- sapply(pi4_j$summaries, "[", 1, 2)
ind[ind4] <- ind[ind4] * pi4_i[nams_i] * pi4_j[nams_j]
}
sum((pi.u.t.i < pi.u.t.j) * c(ind), na.rm = TRUE) / sum(ind, na.rm = TRUE)} else {
NA}
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Hello, I think there may be some problems in the function aucJM， in the follow code,because " if (any(dupl <- duplicated(Time))) { Time[dupl] <- Time[dupl] + runif(length(Time[dupl]), 1e-07, 1e-06) }" only keep the unique event time, which will result in removing subjects whose raw event time less than "Thoriz" using "Ti <= Thoriz" and errors in the estimation of auc. Further, I don't understand the effect of "Time[dupl] <- Time[dupl] + runif(length(Time[dupl]), 1e-07, 1e-06)".
I hope you can answer that for me, thanks very much !