kidney               package:survival               R Documentation

_K_i_d_n_e_y _c_a_t_h_e_t_e_r _d_a_t_a

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

     Data on the recurrence times to infection, at the point of
     insertion of the catheter, for kidney patients using portable
     dialysis equipment. Catheters may be removed for reasons other
     than infection, in which case the observation is censored.  Each
     patient has exactly 2 observations.

     This data has often been used to illustrate the use of random
     effects (frailty) in a survival model.  However, one of the males
     (id 21) is a large outlier, with much longer survival than his
     peers.  If this observation is removed no evidence remains for a
     random subject effect.

_F_o_r_m_a_t:


       patient:  id
       time:     time
       status:   event status
       age:      in years
       sex:      1=male, 2=female
       disease:  disease type (0=GN, 1=AN, 2=PKD, 3=Other)
       frail:    frailty estimate from original paper

_N_o_t_e:

     The original paper ignored the issue of tied times and so is not
     exactly reproduced by the survival package.

_S_o_u_r_c_e:

     CA McGilchrist, CW Aisbett (1991), Regression with frailty in
     survival analysis.  _Biometrics_ *47*, 461-66.

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

     kfit <- coxph(Surv(time, status)~ age + sex + disease + frailty(id), kidney)
     kfit0 <- coxph(Surv(time, status)~ age + sex + disease, kidney)
     kfitm1 <- coxph(Surv(time,status) ~ age + sex + disease + 
                     frailty(id, dist='gauss'), kidney)

