R version 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" 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 the revised model.matrix code > # > test1 <- data.frame(time= c(9, 3,1,1,6,6,8), + status=c(1,NA,1,0,1,1,0), + x= c(0, 2,1,1,1,0,0), + z= factor(c('a', 'a', 'b', 'b', 'c', 'c', 'a')), + stringsAsFactors=FALSE) > > fit1 <- coxph(Surv(time, status) ~ z, test1, iter=1) > fit2 <- coxph(Surv(time, status) ~z, test1, x=T, iter=1) > all.equal(model.matrix(fit1), fit2$x) [1] TRUE > > # This has no level 'b', make sure dummies recode properly > test2 <- data.frame(time= c(9, 3,1,1,6,6,8), + status=c(1,NA,1,0,1,1,0), + x= c(0, 2,1,1,1,0,0), + z= factor(c('a', 'a', 'a', 'a', 'c', 'c', 'a')), + stringsAsFactors=FALSE) > > ftest <- model.frame(fit1, data=test2) > all.equal(levels(ftest$z), levels(test1$z)) [1] TRUE > > # xtest will have one more row than the others, since it does not delete > # the observation with a missing value for status > xtest <- model.matrix(fit1, data=test2) > dummy <- fit2$x > dummy[,1] <- 0 > all.equal(xtest[-2,], dummy, check.attributes=FALSE) [1] TRUE > > # The case of a strata by factor interaction > # Use iter=0 since there are too many covariates and it won't converge > test1$x2 <- factor(rep(1:2, length=7)) > fit3 <- coxph(Surv(time, status) ~ strata(x2)*z, test1, iter=0) > xx <- model.matrix(fit3) > all.equal(attr(xx, "assign"), c(2,2,3,3)) [1] TRUE > all.equal(colnames(xx), c("zb", "zc", "strata(x2)2:zb", + "strata(x2)2:zc")) [1] TRUE > all.equal(attr(xx, "contrasts"), + list("strata(x2)"= "contr.treatment", z="contr.treatment")) [1] TRUE > > fit3b <- coxph(Surv(time, status) ~ strata(x2)*z, test1, iter=0, x=TRUE) > all.equal(fit3b$x, xx) [1] TRUE > > > # A model with a tt term > fit4 <- coxph(Surv(time, status) ~ tt(x) + x, test1, iter=0, + tt = function(x, t, ...) x*t) > ff <- model.frame(fit4) > # There is 1 subject in the final risk set, 4 at risk at time 6, 6 at time 1 > # The .strata. variable numbers from last time point to first > all.equal(ff$.strata., rep(1:3, c(1, 4,6))) [1] TRUE > all.equal(ff[["tt(x)"]], ff$x* c(9,6,1)[ff$.strata.]) [1] TRUE > > xx <- model.matrix(fit4) > all.equal(xx[,1], ff[[2]], check.attributes=FALSE) [1] TRUE > > > proc.time() user system elapsed 0.78 0.12 0.89