survdiff {survival} | R Documentation |
Tests if there is a difference between two or more survival curves using the G-rho family of tests, or for a single curve against a known alternative.
survdiff(formula, data, subset, na.action, rho=0, timefix=TRUE)
formula |
a formula expression as for other survival models, of the form
|
data |
an optional data frame in which to interpret the variables occurring in the formula. |
subset |
expression indicating which subset of the rows of data should be used in the fit. This can be a logical vector (which is replicated to have length equal to the number of observations), a numeric vector indicating which observation numbers are to be included (or excluded if negative), or a character vector of row names to be included. All observations are included by default. |
na.action |
a missing-data filter function. This is applied to the |
rho |
a scalar parameter that controls the type of test. |
timefix |
process times through the |
a list with components:
n |
the number of subjects in each group. |
obs |
the weighted observed number of events in each group. If there are strata, this will be a matrix with one column per stratum. |
exp |
the weighted expected number of events in each group. If there are strata, this will be a matrix with one column per stratum. |
chisq |
the chisquare statistic for a test of equality. |
var |
the variance matrix of the test. |
strata |
optionally, the number of subjects contained in each stratum. |
This function implements the G-rho family of
Harrington and Fleming (1982), with weights on each death of S(t)^rho,
where S is the Kaplan-Meier estimate of survival.
With rho = 0
this is the log-rank or Mantel-Haenszel test,
and with rho = 1
it is equivalent to the Peto & Peto modification
of the Gehan-Wilcoxon test.
If the right hand side of the formula consists only of an offset term,
then a one sample test is done.
To cause missing values in the predictors to be treated as a separate
group, rather than being omitted, use the factor
function with its
exclude
argument.
Harrington, D. P. and Fleming, T. R. (1982). A class of rank test procedures for censored survival data. Biometrika 69, 553-566.
## Two-sample test survdiff(Surv(futime, fustat) ~ rx,data=ovarian) ## Stratified 7-sample test survdiff(Surv(time, status) ~ pat.karno + strata(inst), data=lung) ## Expected survival for heart transplant patients based on ## US mortality tables expect <- survexp(futime ~ 1, data=jasa, cohort=FALSE, rmap= list(age=(accept.dt - birth.dt), sex=1, year=accept.dt), ratetable=survexp.us) ## actual survival is much worse (no surprise) survdiff(Surv(jasa$futime, jasa$fustat) ~ offset(expect))