discSurv (version 2.0.0)

estSurv: Estimated Survival Function

Description

Estimates the survival function S(T = t|x) based on estimated hazard rates. The hazard rates may or may not depend on covariates. The covariates have to be equal across all estimated hazard rates. Therefore the given hazard rates should only vary over time.

Usage

estSurv(haz)

Arguments

haz

Estimated hazard rates ("numeric vector")

Value

Estimated probabilities of survival ("numeric vector")

Details

The argument haz must be given for all intervals [a_0, a_1), [a_1, a_2), ..., [a_q-1, a_q), [a_q, Inf).

References

tutzModelDiscdiscSurv

See Also

estMargProb

Examples

# NOT RUN {

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

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

# Convert to long format
UnempLong <- dataLong(dataShort = subUnempDur, timeColumn = "spell", eventColumn = "censor1")
head(UnempLong)

# Estimate binomial model with logit link
Fit <- glm(formula = y ~ timeInt + age + logwage, data=UnempLong, family = binomial())

# Estimate discrete survival function given age, logwage of first person
hazard <- predict(Fit, newdata = subset(UnempLong, obj == 1), type = "response")
SurvivalFuncCondX <- estSurv(c(hazard, 1))
SurvivalFuncCondX

# }