| kapmeier {epitools} | R Documentation |
Implements product-limit (Kaplan-Meier) method for time-to-event data with censoring.
kapmeier(time, status)
time |
numeric vector with individual observation times |
status |
integer vector indicating status at the end of the observation time: 1 = event, 0 = censored |
This function implements the product-limit method for estimating survival probability for time-to-event data with censoring:
S(t) = product[(nj - dj) / nj] for all tj <= t,
where tj are event times (i.e., times at which one or more events
occur), nj are the number at risk at time tj (by convention,
subjects censored at time tj are considered at-risk and included in
nj), and dj are the number of events at time tj.
A primary purpose of this function was to demonstrate the use of
available R functions to implement a simple statistical method. For example,
kapmeier uses sort, order, duplicated,
tapply, unique, cumprod, cbind, and
dimnames. Studying this function carefully helps one understand
and appreciate the utility of R functions to implement simple methods.
For serious survival analysis load the survival package. The
survfit function in this package implements the product-limit method
and much more. See examples.
Returns an individual-level data frame
Visit http://www.epitools.net for the latest.
Tomas Aragon, aragon@berkeley.edu, http://www.medepi.net/aragon
Selvin S. Statistical Analysis of Epidemiologic Data (Monographs in Epidemiology and Biostatistics, V. 35). Oxford University Press; 3rd edition (May 1, 2004)
See also survfit
##Product-limit method using 'kapmeier' function tt <- c(1,17,20,9,24,16,2,13,10,3) ss <- c(1,1,1,1,0,0,0,1,0,1) round(kapmeier(tt, ss), 3) ##Product-limit method using 'survfit' in 'survival' package library(survival) survfit(Surv(tt, ss)) summary(survfit(Surv(tt, ss)))