nelsonaalen: Cumulative hazard rate or Nelson-Aalen estimator

In mice: Multivariate Imputation by Chained Equations

Cumulative hazard rate or Nelson-Aalen estimator

Description

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.

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.

Value

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

Author(s)

Stef van Buuren, 2012

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.

Examples

require(MASS)

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")

mice documentation built on June 7, 2023, 5:38 p.m.