icmstate (version 0.2.0)

plot.probtrans.subjects: Plot an object of class "probtrans.subjects"

Description

Plots the transition probabilities for a specific subject. Wrapper for plot.probtrans

Usage

# S3 method for probtrans.subjects
plot(x, id, ...)

Arguments

x

An object of class "probtrans.subjects"

id

Subject identifier

...

Further arguments to plot.probtrans

Author

Hein Putter and Daniel Gomon

Details

Note that

Examples

if(require("mstate")){
  data(ebmt3)
  n <- nrow(ebmt3)
  tmat <- transMat(x = list(c(2, 3), c(3), c()), names = c("Tx",
                                                           "PR", "RelDeath"))
  ebmt3$prtime <- ebmt3$prtime/365.25
  ebmt3$rfstime <- ebmt3$rfstime/365.25
  covs <- c("dissub", "age", "drmatch", "tcd", "prtime")
  msbmt <- msprep(time = c(NA, "prtime", "rfstime"), status = c(NA,
                  "prstat", "rfsstat"), data = ebmt3, trans = tmat, keep = covs)
  #Expand covariates so that we can have transition specific covariates
  msbmt <- expand.covs(msbmt, covs, append = TRUE, longnames = FALSE)
  
  #Simple model, transition specific covariates, each transition own baseline hazard
  c1 <- coxph(Surv(Tstart, Tstop, status) ~ dissub1.1 + dissub2.1 +
                age1.1 + age2.1 + drmatch.1 + tcd.1 + dissub1.2 + dissub2.2 +
                age1.2 + age2.2 + drmatch.2 + tcd.2 + dissub1.3 + dissub2.3 +
                age1.3 + age2.3 + drmatch.3 + tcd.3 + strata(trans), data = msbmt,
                method = "breslow")
  #We need to make a data.frame containing all subjects of interest
  ttmat <- to.trans2(tmat)[, c(2, 3, 1)]
  names(ttmat)[3] <- "trans"
  nd_n <- NULL
  for (j in 1:30) {
    # Select global covariates of subject j
    cllj <- ebmt3[j, covs]
    nd2 <- cbind(ttmat, rep(j, 3), rbind(cllj, cllj, cllj))
    colnames(nd2)[4] <- "id"
    # Make nd2 of class msdata to use expand.covs
    attr(nd2, "trans") <- tmat
    class(nd2) <- c("msdata", "data.frame")
    nd2 <- expand.covs(nd2, covs=covs, longnames = FALSE)
    nd_n <- rbind(nd_n, nd2)
   }
   
   icmstate_pt <- probtrans_coxph(c1, predt = 0, direction = "forward", 
                                  newdata = nd_n, trans = tmat)

   #plot transition probabilities for subject 2
   plot(icmstate_pt, id = 2)
}