期刊
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
卷 100, 期 470, 页码 470-483出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/016214504000001420
关键词
correlated failure time data; frailty model; linear transformation model; proportional hazards; semiparametric efficiency; survival data
In this article we study the semiparametric proportional odds model with random effects for correlated, right-censored failure time data. We establish that the maximum likelihood estimators for the parameters of this model are consistent and asymptotically Gaussian. Furthermore, the limiting variances achieve the semiparametric efficiency bounds and can be consistently estimated. Simulation studies show that the asymptotic approximations are accurate for practical sample sizes and that the efficiency gains of the proposed estimators over those of Cai, Cheng, and Wei can be substantial. A real example is provided to illustrate the proposed methods.
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