svycoxph               package:survey               R Documentation

_S_u_r_v_e_y-_w_e_i_g_h_t_e_d _g_e_n_e_r_a_l_i_s_e_d _l_i_n_e_a_r _m_o_d_e_l_s.

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

     Fit a generalised linear model to data from a complex survey
     design, with inverse-probability weighting and with standard
     errors corrected for cluster sampling.

_U_s_a_g_e:

     svycoxph(formula, design,subset=NULL, ...)

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

 formula: Model formula. Any 'cluster()' terms will be ignored.

  design: 'survey.design' object. Must contain all variables in the
          formula

  subset: Expression to select a subpopulation

     ...: Other arguments passed to 'coxph'. 

_D_e_t_a_i_l_s:

     The main difference between this function and 'coxph' in the
     survival package is that this function accounts for the reduction
     in variance from stratified sampling and the increase in variance
     from having only a small number of clusters.

     Note that 'strata' terms in the model formula describe subsets
     that have a separate baseline hazard function and need not have
     anything to do with the stratification of the sampling.

_V_a_l_u_e:

     An object of class 'svycoxph'.

_A_u_t_h_o_r(_s):

     Thomas Lumley

_S_e_e _A_l_s_o:

     'svydesign', 'coxph', 'svyCprod'

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

      

