论文标题
通过风险设置采样的有偏采样数据的COX模型的估计
Estimation for the Cox Model with Biased Sampling Data via Risk Set Sampling
论文作者
论文摘要
普遍的队列抽样通常用于研究疾病很少见的疾病的自然病史，或者通常需要很长时间才能观察到失败事件。但是，众所周知，在这种情况下收集的样本并不代表目标人群，这反过来又导致样本风险集有偏见。此外，当生存时间受到审查时，审查机制是有益的。在本文中，我提出了一种伪 - 派对可能性估计方法，用于通过调整样本风险集，在COX比例危害模型中估算COX比例危害模型中的参数。我研究了由此产生的估计量的渐近特性，并进行了仿真研究，以说明其在提议的方法中的有限样本性能。我还使用提出的方法来分析一组艾滋病毒/艾滋病数据。
Prevalent cohort sampling is commonly used to study the natural history of a disease when the disease is rare or it usually takes a long time to observe the failure event. It is known, however, that the collected sample in this situation is not representative of the target population which in turn leads to biased sample risk sets. In addition, when survival times are subject to censoring, the censoring mechanism is informative. In this paper, I propose a pseudo-partial likelihood estimation method for estimating parameters in the Cox proportional hazards model with right-censored and biased sampling data by adjusting sample risk sets. I study the asymptotic properties of the resulting estimator and conduct a simulation study to illustrate its finite sample performance of the proposed method. I also use the proposed method to analyze a set of HIV/AIDS data.
