survreg               package:survival               R Documentation

_R_e_g_r_e_s_s_i_o_n _f_o_r _a _P_a_r_a_m_e_t_r_i_c _S_u_r_v_i_v_a_l _M_o_d_e_l

_D_e_s_c_r_i_p_t_i_o_n:

     Regression for a parametric survival model. These are all
     time-transformed location models, with the most useful case being
     the accelerated failure models that use a log transformation.

_U_s_a_g_e:

     survreg(formula=formula(data), data=parent.frame(), weights, 
     subset,na.action,dist="weibull",  init=NULL, scale=0,
      control=survreg.control(),parms=NULL,model=FALSE, x=FALSE,
      y=TRUE, robust=FALSE, ...)

_A_r_g_u_m_e_n_t_s:

 formula: a formula expression as for other regression models. See the
          documentation for 'lm' and 'formula' for details. 

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

 weights: Optional observation weights

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

na.action: function to be used to handle any NAs in the data. 

    dist: assumed distribution for y variable.

          If the argument is a character string, then it is assumed to
          name an element from 'survreg.distributions'. These include
          '"weibull"', '"exponential"', '"gaussian"', '"logistic"',
          '"lognormal"' and '"loglogistic"'. Only enough of the name
          needs to be given to make the choice unique.

          Otherwise, it is assumed to be a user defined list conforming
          to the format described in 'survreg.distributions'. 

   parms: a list of fixed parameters.  For the t-distribution for
          instance this is the degrees of freedom; most of the
          distributions have no parameters. 

    init: optional vector of initial values for the parameters. 

   scale: optional fixed value for the scale.  If set to <=0 then the
          scale is estimated. 

 control: a list of control values, in the format producted by
          'survreg.control'. 

   model: if TRUE, the model frame is returned. 

       x: if TRUE, then the X matrix is returned. 

       y: if TRUE, then the y vector (or survival times) is returned. 

  robust: if TRUE, sandwich standard errors are computed. Defaults to
          TRUE when 'formula' contains a 'cluster' term. 

     ...: other arguments which will be passed to 'survreg.control'. 

_V_a_l_u_e:

     an object of class 'survreg' is returned.

_C_o_m_p_a_t_i_b_i_l_i_t_y _n_o_t_e:

     This routine underwent significant changes from survival4 to
     survival5. The survreg.old function gives a backwards-compatible
     interface.  In S-PLUS the new function is called 'survReg' and the
     old one 'survreg'.

_S_e_e _A_l_s_o:

     'survreg.object', 'survreg.distributions', 'pspline', 'frailty',
     'ridge', 'survreg.old'

_E_x_a_m_p_l_e_s:

     ## These are all the same
     survreg(Surv(futime, fustat) ~ ecog.ps + rx, ovarian, dist='weibull',scale=1)
     survreg(Surv(futime, fustat) ~ ecog.ps + rx, ovarian,
     dist="exponential")
     survreg.old(Surv(futime, fustat) ~ ecog.ps + rx, ovarian, dist='extreme',fixed=list(scale=1),link="log")

