survfit.formula {Design}R Documentation

Compute a Survival Curve for Censored Data

Description

Computes an estimate of a survival curve for censored data using either the Kaplan-Meier or the Fleming-Harrington method or computes the predicted survivor function. For competing risks data it computes the cumulative incidence curve.

Usage

## S3 method for class 'formula':
survfit(formula, data, weights, subset, na.action,
        etype, id, conf.type = c("log-log", "log", "plain", "none"),
        ...)

Arguments

formula a formula object, which must have a Surv object as the response on the left of the ~ operator and, if desired, terms separated by + operators on the right. One of the terms may be a strata object. For a single survival curve the right hand side should be ~ 1.
data a data frame in which to interpret the variables named in the formula, subset and weights arguments.
weights The weights must be nonnegative and it is strongly recommended that they be strictly positive, since zero weights are ambiguous, compared to use of the subset argument.
subset expression saying that only a subset of the rows of the data should be used in the fit.
na.action a missing-data filter function, applied to the model frame, after any subset argument has been used. Default is options()$na.action.
etype a variable giving the type of event. Presence of this variable signals the program to compute the cumulative incidece estimate. For each event status==1, the etype variable indicates the type of event. For a censored observation the value of etype is ignored - but do not set it to NA, since that will cause na.action to delete the observation.
id identifies individual subjects, when a given person can have multiple lines of data. when used with the etype variable, this allows the compuation of a cumulative prevalence estimate, i.e., the incidence over time.
conf.type
... Not used

Details

see survfit for details

Value

an object of class "survfit". See survfit.object for details. Methods defined for survfit objects are print, plot, lines, and points.

Author(s)

Thomas Lumley tlumley@u.washington.edu

See Also

survfit.coxph for survival curves from Cox models.

print, plot, lines, coxph, Surv, strata.

Examples

require(survival)
#fit a Kaplan-Meier and plot it
fit <- survfit(Surv(time, status) ~ x, data = aml)
plot(fit, lty = 2:3)
legend(100, .8, c("Maintained", "Nonmaintained"), lty = 2:3)

#fit a Cox proportional hazards model and plot the
#predicted survival for a 60 year old
fit <- coxph(Surv(futime, fustat) ~ age, data = ovarian)
plot(survfit(fit, newdata=data.frame(age=60)),
     xscale=365.25, xlab = "Years", ylab="Survival")

# Here is the data set from Turnbull
#  There are no interval censored subjects, only left-censored (status=3),
#  right-censored (status 0) and observed events (status 1)
#
#                             Time
#                         1    2   3   4
# Type of observation
#           death        12    6   2   3
#          losses         3    2   0   3
#      late entry         2    4   2   5
#
tdata <- data.frame(time  =c(1,1,1,2,2,2,3,3,3,4,4,4),
                    status=rep(c(1,0,2),4),
                    n     =c(12,3,2,6,2,4,2,0,2,3,3,5))
fit  <- survfit(Surv(time, time, status, type='interval') ~1,
              data=tdata, weight=n)

#
# Time to progression/death for patients with monoclonal gammopathy
#  Competing risk curves (cumulative incidence)
fit1 <- survfit(Surv(stop, event=='progression') ~1, data=mgus1,
                    subset=(start==0))
fit2 <- survfit(Surv(stop, status) ~1, data=mgus1,
                    subset=(start==0), etype=event) #competing risks
# CI curves are always plotted from 0 upwards, rather than 1 down
plot(fit2, fun='event', xscale=365.25, xmax=7300, mark.time=FALSE,
            col=2:3, xlab="Years post diagnosis of MGUS")
lines(fit1, fun='event', xscale=365.25, xmax=7300, mark.time=FALSE,
            conf.int=FALSE)
text(10, .4, "Competing Risk: death", col=3)
text(16, .15,"Competing Risk: progression", col=2)
text(15, .30,"KM:prog")

[Package Design version 2.2-0 Index]