# Function to replicate the rows so that each patients' follow-up is split according to all event times (times parameter) up to each patient's end time ```r replicRows(data, tstart, tstop, event, cens, times1, times2, arm) ``` ## Arguments - `data`: a dataframe containing the following variables - `tstart`: the date of the beginning of the follow-up (in numeric format, with the first being equal at 0) - `tstop`: the date of the end of the follow-up (in numeric format) - `event`: the indicator of failure (a death is denoted by 1 at the end of the follow-up) - `cens`: the indicator of treatment censoring (denoted by 1 at the end of the follow-up) - `times1`: a vector of times (in numeric format) indicating the times according to which the rows have to be split for patients in the first arm - `times2`: a vector of times (in numeric format) indicating the times according to which the rows have to be split for patients in the second arm - `arm`: the randomized treatment (2-levels factor) ## Returns a formatted dataframe with the rows replicated according to the provided times parameter ## Examples ```r # To obtain the times parameter, we can apply the timesTokeep function on the same # dataframe in the wide format kept.t <- timesTokeep(toydata, id = "id", tstart = "randt", tstop = "lastdt", mes.cov = list(c("ps1", "ps2", "ps3")), time.cov = list(c("randt", "dt2", "dt3"))) # Now, we can build the long format toy.long <- wideToLongTDC(data = toydata, id = "id", tstart = "randt", tstop = "lastdt", event = "status", bas.cov = c("age", "arm", "swtrtdt"), mes.cov = list(TDconf = c("ps1", "ps2", "ps3")), time.cov = list(c("randt", "dt2", "dt3")), times = kept.t[[1]]) # Put dates in numeric format with tstart at 0 toy.long$tstart <- as.numeric(toy.long$tstart) toy.long$tstop <- as.numeric(toy.long$tstop) toy.long$swtrtdt <- as.numeric(toy.long$swtrtdt) tabi <- split(toy.long, toy.long$id) L.tabi <- length(tabi) tablist <- lapply(1:L.tabi, function(i){ refstart <- tabi[[i]]$tstart[1] tabi[[i]]$tstart <- tabi[[i]]$tstart - refstart tabi[[i]]$tstop <- tabi[[i]]$tstop - refstart tabi[[i]]$swtrtdt <- tabi[[i]]$swtrtdt - refstart return(tabi[[i]]) }) toy.long <- do.call( rbind, tablist ) # Patients are censored when initiating the other arm treatment, that is, at time swtrtdt toy.long2 <- cens.ipw(toy.long, id = "id", tstart = "tstart", tstop = "tstop", event = "event", arm = "arm", realtrt = FALSE, censTime ="swtrtdt") # We collect all event times (death for both arms and treatment censoring according to the trt arm) rep.times1 <- unique(c(toy.long2$tstop[toy.long2$cens==1 & toy.long2$arm == "A"], toy.long2$tstop[toy.long2$event==1])) rep.times2 <- unique(c(toy.long2$tstop[toy.long2$cens==1 & toy.long2$arm == "B"], toy.long2$tstop[toy.long2$event==1])) # to put times in same order as arms levels levels(toy.long2[, "arm"]) # Now, we can replicate the rows toy.rep <- replicRows(toy.long2, tstart = "tstart", tstop = "tstop", event = "event", cens = "cens", times1 = rep.times1, times2 = rep.times2, arm = "arm") toy.rep ``` ## References Graffeo, N., Latouche, A., Le Tourneau C., Chevret, S. (2019) "ipcwswitch: an R package for inverse probability of censoring weighting with an application to switches in clinical trials". Computers in biology and medicine, 111, 103339. doi : "10.1016/j.compbiomed.2019.103339" ## See Also `cens.ipw`, `SHIdat`, `timesTokeep`, `wideToLongTDC`

replicRows function