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Calculates the cumulative hazard rate (Nelson-Aalen estimator)

Usage

nelsonaalen(data, timevar, statusvar)

Arguments

data

A data frame containing the data.

timevar

The name of the time variable in data.

statusvar

The name of the event variable, e.g. death in data.

Value

A vector with nrow(data) elements containing the Nelson-Aalen estimates of the cumulative hazard function.

Details

This function is useful for imputing variables that depend on survival time. White and Royston (2009) suggested using the cumulative hazard to the survival time H0(T) rather than T or log(T) as a predictor in imputation models. See section 7.1 of Van Buuren (2012) for an example.

References

White, I. R., Royston, P. (2009). Imputing missing covariate values for the Cox model. Statistics in Medicine, 28(15), 1982-1998.

Van Buuren, S. (2018). Flexible Imputation of Missing Data. Second Edition. Chapman & Hall/CRC. Boca Raton, FL.

Author

Stef van Buuren, 2012

Examples

require(MASS)
#> Loading required package: MASS
#> 
#> Attaching package: ‘MASS’
#> The following object is masked from ‘package:dplyr’:
#> 
#>     select

leuk$status <- 1 ## no censoring occurs in leuk data (MASS)
ch <- nelsonaalen(leuk, time, status)
plot(x = leuk$time, y = ch, ylab = "Cumulative hazard", xlab = "Time")


### See example on http://www.engineeredsoftware.com/lmar/pe_cum_hazard_function.htm
time <- c(43, 67, 92, 94, 149, rep(149, 7))
status <- c(rep(1, 5), rep(0, 7))
eng <- data.frame(time, status)
ch <- nelsonaalen(eng, time, status)
plot(x = time, y = ch, ylab = "Cumulative hazard", xlab = "Time")