groupkm: Kaplan-Meier Estimates vs. a Continuous Variable

In rms: Regression Modeling Strategies

Kaplan-Meier Estimates vs. a Continuous Variable

Description

Function to divide x (e.g. age, or predicted survival at time u created by survest) into g quantile groups, get Kaplan-Meier estimates at time u (a scaler), and to return a matrix with columns x=mean x in quantile, n=number of subjects, events=no. events, and KM=K-M survival at time u, std.err = s.e. of -log K-M. Confidence intervals are based on -log S(t). Instead of supplying g, the user can supply the minimum number of subjects to have in the quantile group (m, default=50). If cuts is given (e.g. cuts=c(0,.1,.2,...,.9,.1)), it overrides m and g. Calls Therneau's survfitKM in the survival package to get Kaplan-Meiers estimates and standard errors.

Usage

groupkm(x, Srv, m=50, g, cuts, u, 
        pl=FALSE, loglog=FALSE, conf.int=.95, xlab, ylab,
        lty=1, add=FALSE, cex.subtitle=.7, ...)

Arguments

x	variable to stratify
Srv	a Surv object - n x 2 matrix containing survival time and event/censoring 1/0 indicator. Units of measurement come from the "units" attribute of the survival time variable. "Day" is the default.
m	desired minimum number of observations in a group
g	number of quantile groups
cuts	actual cuts in x, e.g. c(0,1,2) to use [0,1), [1,2].
u	time for which to estimate survival
pl	TRUE to plot results
loglog	set to TRUE to plot log(-log(survival)) instead of survival
conf.int	defaults to .95 for 0.95 confidence bars. Set to FALSE to suppress bars.
xlab	if pl=TRUE, is x-axis label. Default is label(x) or name of calling argument
ylab	if pl=TRUE, is y-axis label. Default is constructed from u and time units attribute.
lty	line time for primary line connecting estimates
add	set to TRUE if adding to an existing plot
cex.subtitle	character size for subtitle. Default is .7. Use FALSE to suppress subtitle.
...	plotting parameters to pass to the plot and errbar functions

Value

matrix with columns named x (mean predictor value in interval), n (sample size in interval), events (number of events in interval), KM (Kaplan-Meier estimate), std.err (standard error of -log KM)

See Also

survfit, errbar, cut2, Surv, units

Examples

require(survival)
n <- 1000
set.seed(731)
age <- 50 + 12*rnorm(n)
cens <- 15*runif(n)
h <- .02*exp(.04*(age-50))
d.time <- -log(runif(n))/h
label(d.time) <- 'Follow-up Time'
e <- ifelse(d.time <= cens,1,0)
d.time <- pmin(d.time, cens)
units(d.time) <- "Year"
groupkm(age, Surv(d.time, e), g=10, u=5, pl=TRUE)
#Plot 5-year K-M survival estimates and 0.95 confidence bars by 
#decile of age.  If omit g=10, will have >= 50 obs./group.

rms documentation built on April 12, 2025, 1:18 a.m.