R Under development (unstable) (2024-06-02 r86665 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > ## check that the scale option to summary.survfit works > ## Marc Schwartz reported this as a bug in 2.35-3. > library(survival) > fit <- survfit(Surv(futime, fustat) ~rx, data=ovarian) > temp1 <- summary(fit) > temp2 <- summary(fit, scale=365.25) > > all.equal(temp1$time/365.25, temp2$time) [1] TRUE > all.equal(temp1$rmean.endtime/365.25, temp2$rmean.endtime) [1] TRUE > all.equal(temp1$table[,5:6]/365.25, temp2$table[,5:6]) [1] TRUE > temp <- names(fit) > temp <- temp[!temp %in% c("time", "table", "rmean.endtime")] > all.equal(temp1[temp], temp2[temp]) [1] TRUE > > # Reprise, using the rmean option > temp1 <- summary(fit, rmean=300) > temp2 <- summary(fit, rmean=300, scale=365.25) > all.equal(temp1$time/365.25, temp2$time) [1] TRUE > all.equal(temp1$rmean.endtime/365.25, temp2$rmean.endtime) [1] TRUE > all.equal(temp1$table[,5:6]/365.25, temp2$table[,5:6]) [1] TRUE > all.equal(temp1[temp], temp2[temp]) [1] TRUE > > # Repeat using multi-state data. Time is in months for mgus2 > etime <- with(mgus2, ifelse(pstat==0, futime, ptime)) > event <- with(mgus2, ifelse(pstat==0, 2*death, 1)) > event <- factor(event, 0:2, labels=c("censor", "pcm", "death")) > mfit <- survfit(Surv(etime, event) ~ sex, mgus2) > temp1 <- summary(mfit) > temp2 <- summary(mfit, scale=12) > > all.equal(temp1$time/12, temp2$time) [1] TRUE > all.equal(temp1$rmean.endtime/12, temp2$rmean.endtime) [1] TRUE > all.equal(temp1$table[,3]/12, temp2$table[,3]) [1] TRUE > temp <- names(temp1) > temp <- temp[!temp %in% c("time", "table", "rmean.endtime")] > all.equal(temp1[temp], temp2[temp]) [1] TRUE > > # Reprise, using the rmean option > temp1 <- summary(mfit, rmean=240) > temp2 <- summary(mfit, rmean=240, scale=12) > all.equal(temp1$time/12, temp2$time) [1] TRUE > all.equal(temp1$rmean.endtime/12, temp2$rmean.endtime) [1] TRUE > all.equal(temp1$table[,3]/12, temp2$table[,3]) [1] TRUE > all.equal(temp1[temp], temp2[temp]) [1] TRUE > > > # The n.risk values from summary.survfit were off when there are multiple > # curves (version 2.39-2) > # Verify all components by subscripting > m1 <- mfit[1,] > m2 <- mfit[2,] > s1 <- summary(m1, times=c(0,100, 200, 300)) > s2 <- summary(m2, times=c(0,100, 200, 300)) > s3 <- summary(mfit, times=c(0,100, 200, 300)) > > tfun <- function(what) { + if (is.matrix(s3[[what]])) + all.equal(rbind(s1[[what]], s2[[what]]), s3[[what]]) + else all.equal(c(s1[[what]], s2[[what]]), s3[[what]]) + } > tfun('n') [1] TRUE > tfun("time") [1] TRUE > tfun("n.risk") [1] TRUE > tfun("n.event") [1] TRUE > tfun("n.censor") [1] TRUE > tfun("pstate") [1] TRUE > all.equal(rbind(s1$p0, s2$p0), s3$p0, check.attributes=FALSE) [1] TRUE > tfun("std.err") [1] TRUE > tfun("lower") [1] TRUE > tfun("upper") [1] TRUE > > # Check the cumulative sums > temp <- rbind(0, 0, + colSums(m1$n.event[m1$time <= 100,]), + colSums(m1$n.event[m1$time <= 200, ]), + colSums(m1$n.event[m1$time <= 300, ])) > all.equal(s1$n.event, apply(temp,2, diff)) [1] TRUE > > temp <- rbind(0, 0, + colSums(m2$n.event[m2$time <= 100,]), + colSums(m2$n.event[m2$time <= 200, ]), + colSums(m2$n.event[m2$time <= 300, ])) > all.equal(s2$n.event, apply(temp,2, diff)) [1] TRUE > > temp <- rbind(0, 0, + colSums(m1$n.censor[m1$time <= 100,]), + colSums(m1$n.censor[m1$time <= 200,]), + colSums(m1$n.censor[m1$time <= 300,])) > all.equal(s1$n.censor, apply(temp, 2, diff)) [1] TRUE > > # check the same with survfit objects > s1 <- summary(fit[1], times=c(0, 200, 400, 600)) > s2 <- summary(fit[2], times=c(0, 200, 400, 600)) > s3 <- summary(fit, times=c(0, 200, 400, 600)) > tfun('n') [1] TRUE > tfun("time") [1] TRUE > tfun("n.risk") [1] TRUE > tfun("n.event") [1] TRUE > tfun("n.censor") [1] TRUE > tfun("surv") [1] TRUE > tfun("std.err") [1] TRUE > tfun("lower") [1] TRUE > tfun("upper") [1] TRUE > > f2 <- fit[2] > temp <- c(0, 0, sum(f2$n.event[f2$time <= 200]), + sum(f2$n.event[f2$time <= 400]), + sum(f2$n.event[f2$time <= 600])) > all.equal(s2$n.event, diff(temp)) [1] TRUE > > f1 <- fit[1] > temp <- c(0, 0,sum(f1$n.censor[f1$time <= 200]), + sum(f1$n.censor[f1$time <= 400]), + sum(f1$n.censor[f1$time <= 600])) > all.equal(s1$n.censor, diff(temp)) [1] TRUE > > # > # A check on the censor option > # > s1 <- summary(fit[1]) > s2 <- summary(fit[2]) > s3 <- summary(fit) > tfun('n') [1] TRUE > tfun("time") [1] TRUE > tfun("n.risk") [1] TRUE > tfun("n.event") [1] TRUE > tfun("n.censor") [1] TRUE > tfun("surv") [1] TRUE > tfun("std.err") [1] TRUE > tfun("lower") [1] TRUE > tfun("upper") [1] TRUE > > s1 <- summary(mfit[1,]) > s2 <- summary(mfit[2,]) > s3 <- summary(mfit) > tfun('n') [1] TRUE > tfun("time") [1] TRUE > tfun("n.risk") [1] TRUE > tfun("n.event") [1] TRUE > tfun("n.censor") [1] TRUE > tfun("surv") [1] TRUE > tfun("std.err") [1] TRUE > tfun("lower") [1] TRUE > tfun("upper") [1] TRUE > > proc.time() user system elapsed 0.81 0.14 0.93