survival (version 2.34-1)

summary.survfit: Summary of a Survival Curve

Description

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

Usage

## S3 method for class 'survfit':
summary(object, times, censored=FALSE, scale=1, ...)

Arguments

object

output from a call to survfit.

times

vector of times; the returned matrix will contain 1 row for each time. This must be in increasing order and missing values are not allowed. If censored=T, the default times vector contains all the unique times in fit

censored

logical flag: should the censoring times be included in the output? This is ignored if the times argument is present.

scale

rescale the survival time, e.g., if the input data to survfit were in days, scale=365.25 would scale the output to years.

...

other unused arguments

Value

• a list with the following components
• time
  the timepoint on the curve.
• surv
  the value of the survival curve at time t+0.
• 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.
• 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
  passed through from fit, if present.

See Also

survfit, print.summary.survfit.

Examples

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