SurrogateOutcome (version 1.1)

censor.weight: Calculates censoring probability for weighting

Description

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

Usage

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

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.

Value

Kaplan Meier estimate of survival for censoring at time t

Details

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

Examples

# NOT RUN {
data(ExampleData)
censor.weight(data.x = ExampleData$x1, data.delta = ExampleData$delta1, t=5)

# }