

Surv(survival4)                              R Documentation

_P_a_c_k_a_g_e _a _s_u_r_v_i_v_a_l _v_a_r_i_a_b_l_e

_U_s_a_g_e_:

     Surv(time, event)  or Surv(time, time2, event)

_A_r_g_u_m_e_n_t_s_:

    time: for right censored data, this is the follow up
          time.  For interval data, the first argument is
          the starting time for the interval.

   event: The status indicator, normally 0=alive, 1=dead.
          Other choices are T/F (TRUE = death) or 1/2
          (2=death).  For interval censored data, the status
          indicator is 0=right censored, 1= event at `time',
          2=left censored, 3=interval censored.

   time2: For interval censored  or counting process data
          only, the ending time of the interval.  Intervals
          are assummed to be open on the left and closed on
          the right, (start, end].  For counting process
          data, `event' marks whether an event occured at
          the end of the interval.

    type: one of left, right, counting, interval, or inter-
          val2.  If this is not specified, the default is
          either right or counting, depending on whether the
          `time2' argument is absent or present, respec-
          tively.

  origin: for counting process data, the hazard function
          origin.  This is most often used in conjunction
          with a model containing time dependent strata in
          order to align the subjects properly when they
          cross over from one strata to another.

_V_a_l_u_e_:

     An object of class 'Surv'.  There are methods for
     `print', `is.na', and subscripting survival objects.
     To include a survival object inside a data frame, use
     the `I()' function.  Surv objects are implimented as a
     matrix of 2 or 3 columns.

_M_E_T_H_O_D_:

     In theory it is possible to represent interval censored
     data without a third column containing the explicit
     status.  Exact, right censored, left censored and
     interval censored observation would be represented as
     intervals of (a,a), (a, infinity), (-infinity,b), and
     (a,b) respectively; each specifing the interval within
     which the event is known to have occured.  Infinity is,
     of course, impractical in a computer routine.  If
     `type' is "interval2" then the representation given
     above is assumed, with NA taking the place of infinity.
     If type='interval' then an explicit status code must be
     given in the third argument.  If the status code is 0,
     1 or 2, then the relevant information is assumed to be
     contained in `time',  the value in `time2' is ignored,
     and the second column of the result will contain a
     placeholder.  At present, all of the methods that han-
     dle interval censored data are parametric models, so
     the distinction between open and closed intervals is
     unimportant.  The distinction is important for counting
     process data and the Cox model.

_E_x_a_m_p_l_e_s_:

     data(aml)
     Surv(aml$time, aml$status)

