Helper function; calculates censoring probability needed for inverse probability of censoring weighting
censor.weight(data.x, data.delta, t, weight = NULL, approx = T)
Kaplan Meier estimate of survival for censoring at time t
numeric vector, the observed event time: X = min(T, C) where T is the time of the primary outcome, C is the censoring time
numeric vector of 0/1, the censoring indicator: D = I(T<C) where T is the time of the primary outcome, C is the censoring time
number, the time of interest
a numeric vector or matrix of weights used for perturbation-resampling, default is null.
TRUE or FALSE indicating whether an approximation should be used when calculating the probability of censoring; most relevant in settings where the survival time of interest for the primary outcome is greater than the last observed event but before the last censored case, default is TRUE.
Layla Parast
Computes the Kaplan Meier estimate of survival for the censoring random variable at the specified time