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)

