

Surv(survival5)                              R Documentation

_C_r_e_a_t_e _a _S_u_r_v_i_v_a_l _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n_:

     Create a survival object, usually used as a response
     variable in a model formula.

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

     Surv(time, event)
     or
     Surv(time, time2, event, type=<<see below>>, origin=0)
     is.Surv(x)

_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.

       x: any S-PLUS object.

   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.  Although
          unusual, the event indicator can be omitted, in
          which case all subjects are assumed to have an
          event.

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

    type: character string specifying the type of censoring.
          Possible values are `"right"', `"left"', `"count-
          ing"', `"interval"', or `"interval2"'.  The
          default is `"right"' or `"counting"' depending on
          whether the `time2' argument is absent or present,
          respectively.

  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 implemented as
     a matrix of 2 or 3 columns.

     In the case of `is.Surv', a logical value `T' if `x'
     inherits from class `"Surv"', otherwise an `F'.

_D_E_T_A_I_L_S_:

     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 specifying the interval within
     which the event is known to have occurred.

     If `type = "interval2"' then the representation given
     above is assumed, with NA taking the place of infinity.
     If `type="interval" `event' must be given.  If `event'
     is `0', `1', or `2', 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.

     Presently, the only methods allowing interval censored
     data are the parametric models computed by `survreg',
     so the distinction between open and closed intervals is
     unimportant.  The distinction is important for counting
     process data and the Cox model.

     The function tries to distinguish between the use of
     0/1 and 1/2 coding for left and right censored data
     using `if (max(status)==2)'.  If 1/2 coding is used and
     all the subjects are censored, it will guess wrong.
     Use 0/1 coding in this case.

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

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

