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- _P_r_o_p_o_r_t_i_o_n_a_l _H_a_z_a_r_d_s _R_e_g_r_e_s_s_i_o_n _O_b_j_e_c_t _T_h_i_s _c_l_a_s_s _o_f _o_b_j_e_c_t_s
- _i_s _r_e_t_u_r_n_e_d _b_y _t_h_e _c_o_x_p_h _c_l_a_s_s _o_f _f_u_n_c_t_i_o_n_s _t_o _r_e_p_r_e_s_e_n_t _a
- _f_i_t_t_e_d _p_r_o_p_o_r_t_i_o_n_a_l _h_a_z_a_r_d_s _m_o_d_e_l. _O_b_j_e_c_t_s _o_f _t_h_i_s _c_l_a_s_s
- _h_a_v_e _m_e_t_h_o_d_s _f_o_r _t_h_e _f_u_n_c_t_i_o_n_s _p_r_i_n_t, _s_u_m_m_a_r_y, _r_e_s_i_d_u_a_l_s,
- _p_r_e_d_i_c_t _a_n_d _s_u_r_v_f_i_t.
-
- The following components must be included in a legiti-
- mate coxph object.
-
- _A_r_g_u_m_e_n_t_s:
-
- coefficients:
- the coefficients of the linear predictor, which multi-
- ply the columns of the model matrix. If the model is
- over-determined there will be missing values in the
- vector corresponding to the redundant columns in the
- model matrix.
-
- var:
- the variance matrix of the coefficients. Rows and
- columns corresponding to any missing coefficients are
- set to zero.
-
- naive.var:
- this component will be present only if the robust
- option was true. If so, the var component will contain
- the robust estimate of variance, and this component
- will contain the ordinary estimate.
-
- loglik:
- a vector of length 2 containing the log-likelihood with
- the initial values and with the final values of the
- coefficients.
-
- score:
- value of the efficient score test, at the initial value
- of the coefficients.
-
- iter:
- number of iterations used.
-
- icc:
- the intra-class correlation coefficient. This is only
- present if a cluster term appeared in the model and the
- number of subjects per cluster was >1. It is a vector
- containing the number of clusters, the intra-class
- correlation of the martingale residuals, and the icc of
- the ranked residuals. Because the residuals are
- skewed, the latter may differ from the ordinary icc.
-
- linear.predictors:
- the vector of linear predictors, one per subject.
-
- residuals:
- the martingale residuals.
-
- means:
- vector of column means of the X matrix. Subsequent
- survival curves are adjusted to this value.
-
- n:
- the number of observations used in the fit.
-
- weights:
- the vector of case weights, if one was used.
-
- method:
- the computation method used.
-
- na.action:
- the na.action attribute, if any, that was returned by
- the na.action routine. The object will also contain
- the following, for documentation see the lm object:
- terms, assign, formula, call, and, optionally, x, y,
- and/or frame.
-
- survfit, coxph.detail, cox.zph, survreg,
- residuals.coxph.
-
-