This article discusses regression analysis of multivariate doubly censored data with a wide class of flexible semiparametric transformation frailty models. The proposed models include many commonly used regression models as special cases such as the proportional hazards and proportional odds frailty models. For inference, we propose a nonparametric maximum likelihood estimation method and develop a new expectation–maximization algorithm for its implementation. The proposed estimators of the finite-dimensional parameters are shown to be consistent, asymptotically normal and semiparametrically efficient. We also conduct a simulation study to assess the finite sample performance of the developed estimation method, and the proposed methodology is applied to a set of real data arising from an AIDS study.

中文翻译：

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多元双删失数据的半参数回归分析

本文讨论了使用多种灵活的半参数变换脆弱模型对多元双删失数据进行回归分析。所提出的模型包括许多常用的回归模型作为特殊情况，例如比例风险和比例优势脆弱模型。对于推理，我们提出了一种非参数最大似然估计方法，并为其实现开发了一种新的期望最大化算法。有限维参数的建议估计量被证明是一致的、渐近正态的和半参数有效的。我们还进行了一项模拟研究来评估所开发估计方法的有限样本性能，并将所提出的方法应用于艾滋病研究中的一组真实数据。