期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2003
卷号：65
期号：02
出版社：Indian Statistical Institute
摘要：Some new explicit results are derived for the asymptotic relative efficiency of the semiparametric (partial likelihood) estimates of the regression coefficient and cumulative baseline hazard in Cox's model, relative to those from a correctly specified exponential or Weibull parametric model. It is assumed that the hazard ratio corresponding to the single scalar covariate follows a gamma distribution. Our results generalize those of Miller (1983) for the single sample setting, i.e. without covariates, and of Dabrowska and Doksum (1987), who assumed independence of the survival time from the covariate under the true distribution. It is shown that, in contrast to the results for estimation from partial likelihood, use of the semiparametric estimation model for prediction will usually lead to substantial loss of efficiency
