lungcancer          package:exactRankTests          R Documentation

_L_u_n_g _C_a_n_c_e_r _C_l_i_n_i_c_a_l _T_r_i_a_l

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

     Survival times for patients suffering lung cancer for a treatment
     and control group.

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

     data(lungcancer)

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

     A data frame with 14 observations on the following 3 variables.

     _t_i_m_e survival time in days.

     _c_e_n_s censoring indicator: 0 censored, 1 event.

     _g_r_o_u_p a factor with levels 'control' and 'newdrug'.

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

     The data is given in Table 9.19, page 293, of Metha and Pathel
     (2001). The two-sided p-value for the log-rank test is 0.001 (page
     295).

_R_e_f_e_r_e_n_c_e_s:

     Cyrus R. Mehta & Nitin R. Patel (2001), _StatXact-5 for Windows._
     Manual, Cytel Software Cooperation, Cambridge, USA

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

     data(lungcancer)
     attach(lungcancer)

     # round logrank scores
     scores <- cscores.Surv(cbind(time, cens))
     T <- sum(scores[group=="newdrug"])
     mobs <- sum(group=="newdrug")
     system.time(prob <- pperm(T, scores, m=mobs, al="le"))
     prob
     pperm(T, scores, m=mobs, al="tw")
     pperm(T, scores, m=mobs, al="tw", simulate=TRUE)

     # map into integers, faster
     scores <- cscores.Surv(cbind(time, cens), int=TRUE)
     T <- sum(scores[group=="newdrug"])
     mobs <- sum(group=="newdrug")
     system.time(prob <- pperm(T, scores, m=mobs, al="le"))
     prob
     pperm(T, scores, m=mobs, al="tw")
     pperm(T, scores, m=mobs, al="tw", simulate=TRUE)

     detach(lungcancer)

