rms: groupkm – R documentation

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groupkm

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)

Examples

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

Regression Modeling Strategies

v6.2-0

GPL (>= 2)

Authors

Frank E Harrell Jr <fh@fharrell.com>

Initial release

2021-03-17