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)
cens
the indicator of treatment censoring (denoted by 1 at the end of the follow-up)
arm
the randomized treatment (2-levels factor)
bas.cov
a vector the baseline covariates
conf
a vector of time-dependent confounders
trunc
an optional fraction for the weights. For instance, when trunc = 0.01,
the left tail is truncated to the 1st percentile and the right tail is truncated to the 99th percentile
type
a character string specifying the type of survival curve. The default is type=`kaplan-meier`
Value
the initial dataframe data with stabilized IPCweights as additional arguments. By default, the un-truncated stabilized weights are given. If the trunc option is not NULL then the truncated stabilized weights are also given.
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"
# NOT RUN {## Not run# ipcw(toy.rep, tstart = tstart, tstop = tstop, cens = cens,# arm="arm",# bas.cov = c("age"),# conf = c("TDconf"), trunc = 0.05)# see ?SHIdat for a complete example# }