论文标题
多元生存数据通过Copulas的半参数建模
Semiparametric Modeling for Multivariate Survival Data via Copulas
论文作者
论文摘要
我们提出了一种新的基于Yang and Prentice（YP）模型的边距的多元生存模型。 Ali-Mikhail-Haq（AMH），Clayton，Frank，Gumbel-Hougaard（GH）和Joe Copulas被用来适应边际分布之间的依赖性。基线分布是通过分段指数（PE）分布和伯恩斯坦多项式进行半绘制的。新的模型具有一些吸引人的特征：i）能够考虑到具有穿越生存曲线的生存数据； ii）将众所周知的比例危害（pH）和比例赔率（PO）模型纳入特定情况； iii）更大的灵活性由边际基线分布的半参数建模提供； iv）可能性函数的封闭形式表达式的可用性，从而导致更直接的推论程序。我们进行了一项广泛的蒙特卡洛模拟研究，以评估所提出的模型的性能。最后，我们通过分析涉及诊断患有卵巢癌的患者的生存数据来证明我们的新模型的多功能性。
We propose a new class of multivariate survival models based on archimedean copulas with margins modeled by the Yang and Prentice (YP) model. The Ali-Mikhail-Haq (AMH), Clayton, Frank, Gumbel-Hougaard (GH), and Joe copulas are employed to accommodate the dependency among marginal distributions. Baseline distributions are modeled semiparametrically by the piecewise exponential (PE) distribution and the Bernstein polynomials. The new class of models possesses some attractive features: i) the ability to take into account survival data with crossing survival curves; ii) the inclusion of the well-known proportional hazards (PH) and proportional odds (PO) models as particular cases; iii) greater flexibility provided by the semiparametric modeling of the marginal baseline distributions; iv) the availability of closed-form expressions for the likelihood functions, leading to more straightforward inferential procedures. We conducted an extensive Monte Carlo simulation study to evaluate the performance of the proposed model. Finally, we demonstrate the versatility of our new class of models through the analysis of survival data involving patients diagnosed with ovarian cancer.
