# groupkm

##### Kaplan-Meier Estimates vs. a Continuous Variable

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.

- Keywords
- nonparametric, survival

##### 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

##### Examples

```
# 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.
# }
```

*Documentation reproduced from package rms, version 5.1-3.1, License: GPL (>= 2)*