discSurv (version 1.4.2)

estSurvCens: Estimated Survival Function

Description

Estimates the marginal survival function G(T=t) of the censoring process. Compatible with single event and competing risks data.

Usage

estSurvCens(dataSet, timeColumn, eventColumns)

Arguments

dataSet

Data in original short format (data.frame).

timeColumn

Name of column with discrete time intervals (character scalar).

eventColumns

Names of the event columns of dataSet. In the competing risks case the event columns have to be in dummy encoding format (numeric vectors).

Value

Named vector of estimated survival function of the censoring process for all time points except the last theoretical interval.

References

Gerhard Tutz and Matthias Schmid, (2016), Modeling discrete time-to-event data, Springer series in statistics, Doi: 10.1007/978-3-319-28158-2

See Also

estSurv

Examples

# NOT RUN {
# Load unemployment data
library(Ecdat)
data(UnempDur)

# Select subsample
subUnempDur <- UnempDur [1:100, ]

######################
# Single event example

# Estimate censoring survival function G(t)
estG <- estSurvCens(dataSet=subUnempDur, timeColumn="spell", 
eventColumns="censor1")
estG

#########################
# Competing risks example

# Estimate censoring survival function G(t)
estG <- estSurvCens(dataSet=subUnempDur, timeColumn="spell", 
eventColumns=c("censor1", "censor2", "censor3", "censor4"))
estG

# }