Description Arguments Structure Subscripts Details See Also
This class of objects is returned by the survfit
class of functions
to represent a fitted survival curve.
For a multistate model the object has class c('survfitms', 'survfit')
.
Objects of this class have methods for the functions print
,
summary
, plot
, points
and lines
. The
print.survfit
method does more computation than is typical
for a print method and is documented on a separate page.
n 
total number of subjects in each curve. 
time 
the time points at which the curve has a step. 
n.risk 
the number of subjects at risk at t. 
n.event 
the number of events that occur at time t. 
n.enter 
for counting process data only, the number of subjects that enter at time t. 
n.censor 
for counting process data only, the number of subjects who exit the risk set, without an event, at time t. (For right censored data, this number can be computed from the successive values of the number at risk). 
surv 
the estimate of survival at time t+0. This may be a vector or a matrix. The latter occurs when a set of survival curves is created from a single Cox model, in which case there is one column for each covariate set. 
pstate 
a multistate survival will have the 
std.err 
for a survival curve this contains standard error of the cumulative hazard or log(survival), for a multistate curve it contains the standard error of prev. This difference is a reflection of the fact that each is the natural calculation for that case. 
cumhaz hazard 
optional. Contains the cumulative hazard for each possible transtion. 
strata 
if there are multiple curves, this component gives the number of
elements of the 
upper 
optional upper confidence limit for the survival curve or pstate 
lower 
options lower confidence limit for the survival curve or pstate 
start.time 
optional, the starting time for the curve if other than 0 
p0, sp0 
for a multistate object, the distribution of starting
states. If the curve has a strata dimension, this will be a matrix
one row per stratum. The 
newdata 
for survival curves from a fitted model, this contains the covariate values for the curves 
n.all 
the total number of observations that were available
For counting process data, and any time that the

conf.type 
the approximation used to compute the confidence limits. 
conf.int 
the level of the confidence limits, e.g. 90 or 95%. 
transitions 
for multistate data, the total number of transitions of each type. 
na.action 
the returned value from the na.action function, if any. It will be used in the printout of the curve, e.g., the number of observations deleted due to missing values. 
call 
an image of the call that produced the object. 
type 
type of survival censoring. 
influence.p, influence.c 
optional influence
matrices for the 
version 
the version of the object. Will be missing, 2, or 3 
The following components must be included in a legitimate
survfit
or survfitms
object.
Survfit objects can be subscripted.
This is often used to plot a subset of the curves, for instance.
From the user's point of view the survfit
object appears to be
a vector, matrix, or array of curves.
The first dimension is always the underlying number of curves or
“strata”;
for multistate models the state is always the last dimension.
Predicted curves from a Cox model can have a second dimension
which is the number of different covariate prediction vectors.
The survfit
object has evolved over time: when first created
there was no thought of multistate models for instance. This evolution
has almost entirely been accomplished by the addition of new elements.
One change in survival version 3 is the addition of a survfitconf
routine
which will compute confidence intervals for a survfit
object.
This allows the computation of CI intervals to be deferred until later,
if desired, rather than making them a permanent part of the object.
Later iterations of the base routines may omit the confidence intervals.
The survfit object starts at the first observation time, but survival
curves are normally plotted from time 0.
A helper routine survfit0
can be used to add this first time point
and align the data.
plot.survfit
,
summary.survfit
,
print.survfit
,
survfit
,
survfit0
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