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"'. 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")

