estSurvCens: Estimated Survival Function of Censoring Process

In discSurv: Discrete Time Survival Analysis

Estimated Survival Function of Censoring Process

Description

Estimates the marginal survival function G(T=t) of the censoring process based on a life table estimator. Compatible with single event and competing risks data.

Usage

estSurvCens(dataShort, timeColumn, eventColumns)

Arguments

dataShort	Data in original short format ("class data.frame").
timeColumn	Name of column with discrete time intervals ("character vector").
eventColumns	Names of the event columns of dataShort("character vector"). In the competing risks case the event columns have to be in dummy encoding format ("numeric vector").

Value

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

Note

In the censoring survival function the last time interval [a_q, Inf) has the probability of zero.

Author(s)

Thomas Welchowski [e-mail]

References

\insertRef

tutzModelDiscdiscSurv

See Also

estSurv

Examples

# Load unemployment data
library(Ecdat)
data(UnempDur)

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

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

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

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

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

discSurv documentation built on March 18, 2022, 7:12 p.m.