R Under development (unstable) (2023-08-12 r84939 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 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. > # Understanding edge cases > library(survival) > > # > # this is from a user report of a problem with cumevents. When there is > # a row merged in that is a censor, don't mark it as a cumevent. > # > base <- data.frame( + id = 1:2, tstart = c(0, 0), tstop = c(10, 10), got_flu = c(0, 0), + has_flu = factor(c("no", "no"), levels = c("no", "yes"))) > base <- tmerge(base, base, id = id, got_flu = event(tstop, got_flu)) > > # add time-varying covariates > vars <- data.frame(id = c(1, rep(2, 5)), time = c(0, (0:4) * 2), x = rnorm(6)) > base <- tmerge(base, vars, id = id, x = tdc(time, x)) > > # add cumevents, using a covariate > events <- data.frame( + id = c(2, 2, 2), + # notice the zero -- the second row should not add an event + got_flu = c(1,0,2), + has_flu = c("yes", "no", "yes"), + time = c(3, 5, 8)) > b2 <- tmerge(base, events, id = id, got_flu = cumevent(time, got_flu), + has_flu = tdc(time, has_flu)) Warning message: In tmerge(base, events, id = id, got_flu = cumevent(time, got_flu), : replacement of variable 'has_flu' > > all.equal(b2$got_flu, c(0,0,1,0,0,0,3,0)) [1] TRUE > > > # Tied times in the merger data set > # for all of them missings are essentially ignored > # last obs wins for tdc and event > tiedat <- data.frame(id=c(1, 1, 1, 2,2,2), time=c(3,4, 4, 3, 5, 5), + x=c(1, NA,0, 2,3,4)) > b3 <- tmerge(base, tiedat, id=id, x1= tdc(time, x), x2=cumtdc(time, x), + x3= event(time, x), x4 = cumevent(time, x)) > all.equal(b3$x1, c(NA, 1, 0, NA, NA, 2,2, 4,4,4)) [1] TRUE > all.equal(b3$x2, c(NA, 1, 1, NA, NA, 2,2, 9,9,9)) [1] TRUE > all.equal(b3$x3, c(1,0,0,0,2,0,4,0,0,0)) [1] TRUE > all.equal(b3$x4, c(1,0,0,0,2,0,9,0,0,0)) [1] TRUE > > # Multiple overlapping time windows in the first step. > # Should generate an error message > test <- tryCatch( + {tmerge(pbcseq[, c("id", "trt", "age", "sex")], pbcseq, id, + death = event(futime, status==2))}, + error= function(cond) { + if (grepl("duplicate identifiers", cond)) + cat("successful tmerge error test\n") + } + ) successful tmerge error test > > # Using a tdc that depends on more than one variable. If they are not > # exactly the same class, tmerge should fail. > # Happens with wide data sets > > tdata <- data.frame(id= 1:3, age=c(40,44,38), dtime=c(700, 600, 500), + t1 = c(111, 211, 311), x1= as.integer(c(4, 5, 6)), + t2 = c(120, 240, 400.3), x2=c( 9, 8, 7), + t3 = c(400, 500, 450), x3=c(12,2, 0)) > # This works > wide1 <- tmerge(tdata[,1:2], tdata, id=id, death= event(dtime), + x = tdc(t1, x1), x= tdc(t2, x2), x= tdc(t3, x3)) > > r1 <- data.frame(id=rep(1:3, each=4), + age= tdata$age[rep(1:3, each=4)], + tstart=c(0,111, 120, 400, 0, 211, 240, 500, 0, 311,400.3, 450), + tstop =c(111, 120, 400, 700, 211, 240, 500, 600, + 311, 400.3, 450, 500), + death= rep(c(0,0,0,1), 3), + x= c(NA,4, 9,12, NA, 5, 8, 2, NA, 6,7, 0)) > all.equal(r1, wide1, check.attributes=FALSE) [1] TRUE > > tdata$x2[2] <- 'c' # different data type > test <- tryCatch( + {tmerge(tdata[,1:2], tdata, id=id, death= event(dtime), + x = tdc(t1, x1), x= tdc(t2, x2), x= tdc(t3, x3))}, + error= function(cond) { + if (grepl("tdc update does not match prior variable type: x", cond)) + cat("successful tmerge error test\n") + } + ) successful tmerge error test > > proc.time() user system elapsed 1.42 0.04 1.46