Maximum likelihood estimation for the proportional odds model with random effects
Maximum likelihood estimation for the proportional odds model with random effects
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DOI：
10.1198/016214504000001420
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发表时间：
2005-06-01
影响因子：
3.7
通讯作者：
Yin, GS
中科院分区：
文献类型：
--
作者：
Zeng, DL;Lin, DY;Yin, GS
本文研究了具有随机效应的半参数比例优势模型。我们建立了这个模型的参数的极大似然估计是一致的和渐近高斯。此外，极限方差达到半参数效率界，可以一致地估计。模拟研究表明，渐近近似是准确的实际样本量和效率增益的建议估计超过蔡，程，魏可以是实质性的。最后给出了一个真实的例子来说明所提出的方法。
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.