Returns a list containing the survival curve, confidence limits for the curve, and other information.

```
# S3 method for survfit
summary(object, times, censored=FALSE, scale=1,
extend=FALSE, rmean=getOption('survfit.rmean'), ...)
```

a list with the following components:

- surv
the estimate of survival at time t+0.

- time
the timepoints on the curve.

- n.risk
the number of subjects at risk at time t-0 (but see the comments on weights in the

`survfit`

help file).- n.event
if the

`times`

argument is missing, then this column is the number of events that occurred at time t. Otherwise, it is the cumulative number of events that have occurred since the last time listed until time t+0.- n.entered
This is present only for counting process survival data. If the

`times`

argument is missing, this column is the number of subjects that entered at time t. Otherwise, it is the cumulative number of subjects that have entered since the last time listed until time t.- n.exit.censored
if the

`times`

argument is missing, this column is the number of subjects that left without an event at time t. Otherwise, it is the cumulative number of subjects that have left without an event since the last time listed until time t+0. This is only present for counting process survival data.- std.err
the standard error of the survival value.

- conf.int
level of confidence for the confidence intervals of survival.

- lower
lower confidence limits for the curve.

- upper
upper confidence limits for the curve.

- strata
indicates stratification of curve estimation. If

`strata`

is not`NULL`

, there are multiple curves in the result and the`surv`

,`time`

,`n.risk`

, etc. vectors will contain multiple curves, pasted end to end. The levels of`strata`

(a factor) are the labels for the curves.- call
the statement used to create the

`fit`

object.- na.action
same as for

`fit`

, if present.- table
table of information that is returned from

`print.survfit`

function.- type
type of data censoring. Passed through from the fit object.

- object
the result of a call to the

`survfit`

function.- times
vector of times; the returned matrix will contain 1 row for each time. The vector will be sorted into increasing order; missing values are not allowed. If

`censored=T`

, the default`times`

vector contains all the unique times in`fit`

, otherwise the default`times`

vector uses only the event (death) times.- censored
logical value: should the censoring times be included in the output? This is ignored if the

`times`

argument is present.- scale
numeric value to rescale the survival time, e.g., if the input data to

`survfit`

were in days,`scale = 365.25`

would scale the output to years.- extend
logical value: if TRUE, prints information for all specified

`times`

, even if there are no subjects left at the end of the specified`times`

. This is only used if the`times`

argument is present.- rmean
Show restricted mean: see

`print.survfit`

for details- ...
for future methods

This routine has two uses: printing out a survival curve at specified
time points (often yearly), or extracting the values at specified time
points for further processing.
In the first case we normally want `extend=FALSE`

, i.e., don't print out
data past the end of the curve. If the `times`

option only
contains values beyond the last point in the curve then there is nothing
to print and an error message will result.
For the second usage we almost always want `extend=TRUE`

, so that the
results will have a predictable length.

The `survfit`

object itself will have a row of information at each
censoring or event time, it does not save information on each unique
entry time. For printout at two time points t1, t2, this function will
give the the number at risk at the smallest event times that are >= t1
and >= t2, respectively, the survival curve at the largest recorded times
<= t1 and <= t2, and the number of events and censorings in the interval
t1 < t <= t2.

When the routine is called with counting process data many users are
confused by counts that are too large.
For example, `Surv(c(0,0, 5, 5), c(2, 3, 8, 10), c(1, 0, 1, 0))`

followed by a request for the values at time 4.
The `survfit`

object has entries only at times 2, 3, 8, and 10;
there are 2 subjects at risk at time 8, so that is what will be printed.

`survfit`

, `print.summary.survfit`

```
summary( survfit( Surv(futime, fustat)~1, data=ovarian))
summary( survfit( Surv(futime, fustat)~rx, data=ovarian))
```

Run the code above in your browser using DataLab