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. > options(na.action=na.exclude) # preserve missings > options(contrasts=c('contr.treatment', 'contr.poly')) #ensure constrast type > library(survival) > > # > # Test out subscripting in the case of a coxph survival curve > # > aeq <- function(x,y, ...) all.equal(as.vector(x), as.vector(y), ...) > > fit <- coxph(Surv(time, status) ~ age + sex + meal.cal + strata(ph.ecog), + data=lung) > surv1 <- survfit(fit) > temp <- surv1[2:3] > > which <- cumsum(surv1$strata) > zed <- (which[1]+1):(which[3]) > aeq(surv1$surv[zed], temp$surv) [1] TRUE > aeq(surv1$time[zed], temp$time) [1] TRUE > > # This call should not create a model frame in the code -- so same > # answer but a different path through the underlying code > fit <- coxph(Surv(time, status) ~ age + sex + meal.cal + strata(ph.ecog), + x=T, data=lung) > surv2 <- survfit(fit) > all.equal(surv1, surv2) [1] TRUE > > # > # Now a result with a matrix of survival curves > # > dummy <- data.frame(age=c(30,40,60), sex=c(1,2,2), meal.cal=c(500, 1000, 1500)) > surv2 <- survfit(fit, newdata=dummy) > > zed <- 1:which[1] > aeq(surv2$surv[zed,1], surv2[1,1]$surv) [1] TRUE > aeq(surv2$surv[zed,2], surv2[1,2]$surv) [1] TRUE > aeq(surv2$surv[zed,3], surv2[1,3]$surv) [1] TRUE > aeq(surv2$surv[zed, ], surv2[1,1:3]$surv) [1] TRUE > aeq(surv2$surv[zed], (surv2[1])$surv) [1] TRUE > aeq(surv2$surv[zed, ], surv2[1, ]$surv) [1] TRUE > > # And the depreciated form - call with a named vector as 'newdata' > # the resulting $call component won't match so delete it before comparing > # newdata will have mismatched row names due to subscripting > surv3 <- survfit(fit, c(age=40, sex=2, meal.cal=1000)) > keep <- which(!(names(surv3) %in% c("newdata", "call"))) > all.equal(unclass(surv2[,2])[keep], unclass(surv3)[keep]) [1] TRUE > > # Test out offsets, which have recently become popular due to a Langholz paper > fit1 <- coxph(Surv(time, status) ~ age + ph.ecog, lung) > fit2 <- coxph(Surv(time, status) ~ age + offset(ph.ecog * fit1$coefficients[2]), lung) > > surv1 <- survfit(fit1, newdata=data.frame(age=50, ph.ecog=1)) > surv2 <- survfit(fit2, newdata=data.frame(age=50, ph.ecog=1)) > all.equal(surv1$surv, surv2$surv) [1] TRUE > > # And a model with only offsets. > eta <- cbind(lung$age, lung$ph.ecog) %*% coef(fit1) > fit3 <- coxph(Surv(time, status) ~ offset(eta), lung) > aeq(fit3$loglik, fit1$loglik[2]) [1] TRUE > > surv3 <- survfit(fit3, newdata=data.frame(eta= 50*fit1$coefficients[1] + fit1$coefficients[2])) > all.equal(surv3$surv, surv1$surv) [1] TRUE > > # > # Check out the start.time option > # > surv3 <- survfit(fit1, newdata=data.frame(age=50, ph.ecog=1), + start.time=100) > index <- match(surv3$time, surv1$time) > rescale <- summary(surv1, times=100)$surv > all.equal(surv3$surv, surv1$surv[index]/rescale) [1] TRUE > > > proc.time() user system elapsed 0.81 0.12 0.93