survobrien             package:survival             R Documentation

_O'_B_r_i_e_n'_s _T_e_s_t _f_o_r _A_s_s_o_c_i_a_t_i_o_n _o_f _a _S_i_n_g_l_e _V_a_r_i_a_b_l_e _w_i_t_h _S_u_r_v_i_v_a_l

_D_e_s_c_r_i_p_t_i_o_n:

     Peter O'Brien's test for association of a single variable with
     survival This test is proposed in Biometrics, June 1978.

_U_s_a_g_e:

     survobrien(formula, data)

_A_r_g_u_m_e_n_t_s:

 formula: a valid formula for a cox model, without time dependent
          covariates. 

    data: a data frame. 

_V_a_l_u_e:

     a new data frame.  The original time and status variables are
     removed, and have been replaced with 'start', 'stop', and 'event'.
      If a predictor variable is a factor or is protected with 'I()',
     it is retained as is.  Other predictor variables have been
     replaced with time-dependent logit scores.

     Because of the time dependent variables, the new data frame will
     have many more rows that the original data, approximately #rows *
     #deaths /2.

_M_E_T_H_O_D:

     A time-dependent cox model can now be fit to the new data. The
     univariate statistic, as originally proposed, is equivalent to
     single variable score tests from the time-dependent model. This
     equivalence is the rationale for using the time dependent model as
     a multivariate extension of the original paper.

     In O'Brien's method, the x variables are re-ranked at each death
     time.  A simpler method, proposed by Prentice, ranks the data only
     once at the start. The results are usually similar.

_R_e_f_e_r_e_n_c_e_s:

     O'Brien, Peter, "A Nonparametric Test for Association with
     Censored Data", _Biometrics_ 34: 243-250, 1978.

_S_e_e _A_l_s_o:

     'survdiff'

_E_x_a_m_p_l_e_s:

     xx <- survobrien(Surv(futime, fustat) ~ age + factor(rx) + I(ecog.ps),
                                    data=ovarian)
     coxph(Surv(start, stop, event) ~ age, data=xx)
     coxph(Surv(start, stop, event) ~ age + rx + ecog.ps, data=xx)

