

   TTeesstt SSuurrvviivvaall CCuurrvvee DDiiffffeerreenncceess

        survdiff(formula, data,  rho=0, subset)

   AArrgguummeennttss::

    formula: a formula expression as for other survival models,
             of the form `Surv(time, status) ~ predictors'.
             For a one-sample test, the predictors must consist
             of a single `offset(sp)' term, where sp is a vec-
             tor giving the survival probability of each sub-
             ject.  For a k-sample test, each unique combina-
             tion of predictors defines a subgroup.  To cause
             missing values in the predictors to be treated as
             a separate group, rather than being omitted, use
             the `strata' function with its `na.group=T' argu-
             ment.

       data: an optional data frame in which to interpret the
             variables occurring in the formula.

        rho: a parameter that controls the type of test.

     subset: subset of the observations to be used in the fit.

          n: the number of subjects in each group.

        obs: the weighted observed number of events in each
             group.

        exp: the weighted expected number of events in each
             group.

      chisq: the chisquare statistic for a test of equality.

   VVaalluuee::

        a list with components:

   MMEETTHHOODD::

        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.  When `rho = 0' this is the log-rank or Man-
        tel-Haenszel test, and when `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.

   RReeffeerreenncceess::

        Harrington, D. P. and Fleming, T. R. (1982).  A class
        of rank test procedures for censored survival data.
        Biometrika 69, 553-566.

   SSeeee AAllssoo::

        `survdiff.print'.

   EExxaammpplleess::

        survdiff(Surv(futime, fustat) ~ rx)

        expect <- survexp(entry, birth, sex, futime)
        survdiff(Surv(futime, fustat) ~ offset(expect$surv))  #One sample log-rank

