## S3 method for class 'survfit':
print(x, scale=1, digits = max(options()$digits - 4,3),
print.rmean=getOption("survfit.print.rmean"),
rmean = getOption('survfit.rmean'),...)
survfit
function.scale=365
would scale the printout to years.table
component of summary.survfit
.)rmean
) and its standard error, are printed.
If there are multiple curves, there is one line of output for each.rmean
option.
The first is to set the upper limit to a constant, e.g.,rmean=365
.
In this case the reported mean would be the expected number of days, out
of the first 365, that would be experienced by each group. This is
useful if interest focuses on a fixed period.
Other options are "none"
(no estimate), "common"
and
"individual"
.
The "common"
option uses the maximum time for all curves in the
object as a common upper limit for the auc calculation.
For the "individual"
options the mean is computed as the area
under each curve,
over the range from 0 to the maximum observed time for that curve.
Since the end point is random, values for different curves are not
comparable and the printed standard errors are an underestimate as
they do not take into account this random variation. This option is
provided mainly for backwards compatability, as this estimate was the
default (only) one in earlier releases of the code.
Note that SAS (as of version 9.3) uses the integral up to the last
event time of each individual curve; we consider this the worst
of the choices and do not provide an option for that calculation.The median and its confidence interval are defined by drawing a horizontal line at 0.5 on the plot of the survival curve and its confidence bands. The intersection of the line with the lower CI band defines the lower limit for the median's interval, and similarly for the upper band. If any of the intersections is not a point, then we use the smallest point of intersection, e.g., if the survival curve were exactly equal to 0.5 over an interval.
summary.survfit
, quantile.survfit