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.

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

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

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`

)

# NOT RUN { 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. # }