survfitr               package:survrec               R Documentation

_C_o_m_p_u_t_e _a _S_u_r_v_i_v_a_l _C_u_r_v_e _f_o_r _R_e_c_u_r_r_e_n_t _E_v_e_n_t _D_a_t_a _g_i_v_e_n _a _c_o_v_a_r_i_a_t_e

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

     Computes an estimate of a survival curve for recurrent event data
     using either  the Pea-Strawderman-Hollander, Wang-Chang or MLE
     Frailty estimators. It also computes the asymptotic standard
     errors. The resulting object  of class "survfitr" is plotted by
     `plot.survfitr', before it is returned.

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

     survfitr(formula, data, type="MLEfrailty",...) 

_A_r_g_u_m_e_n_t_s:

 formula: A formula object. If a formula object is supplied it must
          have a Survr object as the response on the left of the ~
          operator and a term on the right. For a single survival curve
          the "~1" part of the formula is required.  

    data: a data frame in wich to interpret the variables named in the
          formula.

    type: a character string specifying the type of survival curve.
          Possible value are "pena-strawderman-hollander", "wang-chang"
          or "MLEfrailty". The default is "MLEfrailty". Only the first
          words are required, e.g "pe","wa","ML"

     ...: 

     {additional arguments passed to the type of estimator. }

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

     See the help details of psh.fit, wc.fit or mlefrailty depending on
     the type chosen

_V_a_l_u_e:

     a survfitr object. Methods defined for survfitr objects are
     provided for print,plot,lines  and summary.

_N_o_t_e:

     The mantainer wishes to thank Professors Chiung-Yu Huang and
     Shu-Hui Chang for their help for providing us with the Fortran
     code which computes standard errors of Wang and Chang's estimator.

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

     1. Pea, E.A., Strawderman, R. and Hollander, M. (2001).
     Nonparametric Estimation with Recurrent Event Data.  _J. Amer.
     Statist. Assoc_ *96*, 1299-1315. 
      2. Wang, M.-C. and Chang, S.-H. (1999). Nonparametric Estimation
     of a Recurrent Survival Function. _J. Amer. Statist. Assoc_ *94*,
     146-153.

_S_e_e _A_l_s_o:

     'print.survfitr','plot.survfitr', 'lines.survfitr',
     'summary.survfitr', 'Survr','psh.fit','wc.fit', 'mlefrailty.fit'

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

       data(colon)
       # fit a pena-strawderman-hollander and plot it
       fit<-survfitr(Survr(hc,time,event)~as.factor(dukes),data=colon,type="pena")
       plot(fit,ylim=c(0,1),xlim=c(0,2000))
       # print the survival estimators
       fit
       summary(fit)

       # fit a MLE Frailty and plot it (in this case do not show s.e.)
       fit<-survfitr(Survr(hc,time,event)~as.factor(dukes),data=colon,type="MLE")
       plot(fit)
       # print the survival estimators
       fit
       summary(fit)

