Surv                package:survival                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=, 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"', '"counting"', '"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.   'Surv' objects are
     implemented as a matrix of 2 or 3 columns.

     In the case of 'is.Surv', a logical value 'TRUE' if 'x' inherits
     from  class '"Surv"', otherwise an 'FALSE'.

_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.

_S_e_e _A_l_s_o:

     'coxph', 'survfit', 'survreg'.

_E_x_a_m_p_l_e_s:

     with(aml, Surv(time, status))
     with(heart, Surv(start,stop,event))

