# groupkm

From rms v2.0-2
by Frank E Harrell Jr

##### 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`

)

##### concept

- grouping
- stratification
- aggregation

##### See Also

##### 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.
```

*Documentation reproduced from package rms, version 2.0-2, License: GPL (>= 2)*

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