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-
- _G_r_a_p_h_i_c_a_l _t_e_s_t _o_f _p_r_o_p_o_r_t_i_o_n_a_l _h_a_z_a_r_d_s _D_i_s_p_l_a_y_s _a _g_r_a_p_h _o_f
- _t_h_e _s_c_a_l_e_d _S_h_o_e_n_f_e_l_d _r_e_s_i_d_u_a_l_s, _a_l_o_n_g _w_i_t_h _a _s_m_o_o_t_h.
-
- plot.cox.zph(x, resid=T, se=T, df=4, nsmo=40, var)
-
- _A_r_g_u_m_e_n_t_s:
-
- x:
- result of the cox.zph function.
-
- resid:
- include the residuals on the plot, as well as the
- smooth fit.
-
- se:
- if true, confidence bands at 2 standard errors will be
- added.
-
- df:
- the degrees of freedom for the fitted natural spline.
- A df value of 2 leads to a linear fit.
-
- nsmo:
- number of points used to plot the fitted spline.
-
- var:
- the set of variables for which plots are desired. By
- default, plots are produced in turn for each variable
- of a model. Selection of a single variable allows
- other features to be added to the plot, e.g., a hor-
- izontal line at zero or a main title. This has been
- superseded by a subscripting method; see the example
- below.
-
- a plot is produced on the current graphics device.
-
- cox.zph, coxph
-
- _E_x_a_m_p_l_e_s:
-
- vfit <- coxph(Surv(futime,fustat) ~ rx + factor(celltype) + karno +age,
- data=veteran, x=T)
- temp <- cox.zph(vfit)
- plot(temp[5]) #do only the Karnofsky score plot
- #plot(temp, var=5) # old way of doing the prior command
- abline(0,0, lty=3)
- lines( lm( temp[,5] ~ temp), lty=4) #Add the linear fit as well
- title(main="VA Lung Study")
-
-