survexp.fit             package:survival             R Documentation

_W_o_r_k _F_u_n_c_t_i_o_n _t_o _C_o_m_p_u_t_e _E_x_p_e_c_t_e_d _S_u_r_v_i_v_a_l

_D_e_s_c_r_i_p_t_i_o_n:

     Compute expected survival. This function is not to be called by
     the user.

_U_s_a_g_e:

     survexp.fit(x, y, times, death, ratetable)

_A_r_g_u_m_e_n_t_s:

       x: a matrix. The first column contains the group, an integer
          value that divides the subjects into subsets. Remaining
          columns must match the dimensions of the 'ratetable', in the
          correct order. 

       y: the follow up time for each subject. 

   times: the vector of times at which a result will be computed. 

   death: death indicator

ratetable: a rate table, such as 'survexp.uswhite'. 

_D_e_t_a_i_l_s:

     For cohort survival it must be the potential censoring time for
     each subject, ignoring death.

     For an exact estimate 'times' should be a superset of 'y', so that
     each subject at risk is at risk for the entire sub-interval of
     time. For a large data set, however, this can use an inordinate
     amount of storage and/or compute time.  If the 'times' spacing is
     more coarse than this, an actuarial approximation is used which
     should, however, be extremely accurate as long as all of the
     returned values are > .99.

     For a subgroup of size 1 and 'times' > 'y', the conditional method
     reduces to exp(-h) where h is the expected cumulative hazard for
     the subject over his/her observation time.  This is used to
     compute individual expected survival.

_V_a_l_u_e:

     A list containing the number of subjects and the expected
     survival(s) at each time point. If there are multiple groups,
     these will be matrices with one column per group.

_W_A_R_N_I_N_G:

     Most users will call the higher level routine 'survexp'.
     Consequently, this function has very few error checks on its input
     arguments.

_S_e_e _A_l_s_o:

     'survexp', 'survexp.us'