Wrapper function for survtmle that takes a fitted
survtmle object and computes the TMLE estimated incidence for all
times specified in the times argument. For this function to work,
the original call to survtmle should have been executed with
returnModels = TRUE. This allows the function to be more efficient
than repeated calls to survtmle in that
timepoints will use fitted censoring (and hazard if
method="hazard" was used in the original call) estimates. It is
therefore advisable that the vector times used in the call to
timepoints not include times beyond the time specified in
t0 in the original call to survtmle. This can be
ensured be making the original call to survtmle with
t0 = max(ftime).
timepoints(object, times, returnModels = FALSE)
| object | A fitted |
|---|---|
| times | The times to evaluate incidence. |
| returnModels | Should the function return fitted GLM or Super Learner
models at each timepoint. If set to |
An object of class tp.survtmle with number of entries equal
to length(times). Each entry is named "tX", where X denotes a single
value of times.
# simulate data set.seed(1234) n <- 100 ftime <- round(runif(n, 1, 4)) ftype <- round(runif(n, 0, 2)) trt <- rbinom(n, 1, 0.5) adjustVars <- data.frame(W1 = rnorm(n), W2 = rnorm(n)) # fit an initial survtmle object with t0=max(ftime) fm <- survtmle( ftime = ftime, ftype = ftype, trt = trt, adjustVars = adjustVars, glm.trt = "1", glm.ftime = "trt + W1 + W2", glm.ctime = "trt + W1 + W2", method = "mean", returnModels = TRUE ) # call timepoints to get cumulative incidence estimates at each timepoint allTimes <- timepoints(object = fm, times = 1:4, returnModels = FALSE) # look at results for time 1 class(allTimes$t1)#> [1] "survtmle"allTimes$t1#> $est #> [,1] #> 0 1 0.11420933 #> 1 1 0.08893310 #> 0 2 0.09813023 #> 1 2 0.02051795 #> #> $var #> 0 1 1 1 0 2 1 2 #> 0 1 1.851155e-03 3.343729e-05 -1.918862e-04 -4.921541e-06 #> 1 1 3.343729e-05 1.679328e-03 -1.913208e-05 -3.350074e-05 #> 0 2 -1.918862e-04 -1.913208e-05 1.933470e-03 5.318150e-09 #> 1 2 -4.921541e-06 -3.350074e-05 5.318150e-09 3.632602e-04 #># look at results for time 2 allTimes$t2#> $est #> [,1] #> 0 1 0.2725236 #> 1 1 0.2440495 #> 0 2 0.1758847 #> 1 2 0.2003141 #> #> $var #> 0 1 1 1 0 2 1 2 #> 0 1 4.513203e-03 6.160159e-05 -9.378340e-04 5.297656e-05 #> 1 1 6.160159e-05 4.270541e-03 -8.875712e-05 -1.167929e-03 #> 0 2 -9.378340e-04 -8.875712e-05 3.664619e-03 1.676504e-05 #> 1 2 5.297656e-05 -1.167929e-03 1.676504e-05 3.802279e-03 #>