censor.weight: Calculates censoring probability for weighting

In Rsurrogate: Robust Estimation of the Proportion of Treatment Effect Explained by Surrogate Marker Information

Description

Helper function; calculates censoring probability needed for inverse probability of censoring weighting

Usage

censor.weight(data.x, data.delta, t, weight = NULL, approx = T)

Arguments

data.x	numeric vector, the observed event time: X = min(T, C) where T is the time of the primary outcome, C is the censoring time
data.delta	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
t	number, the time of interest
weight	a numeric vector or matrix of weights used for perturbation-resampling, default is null.
approx	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.

Details

Computes the Kaplan Meier estimate of survival for the censoring random variable at the specified time

Value

Kaplan Meier estimate of survival for censoring at time t

Author(s)

Layla Parast

Rsurrogate documentation built on Nov. 14, 2021, 9:07 a.m.