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Comparison of estimators in nested case-control studies with multiple outcomes

机译：嵌套病例对照研究中有多个结果的估计量的比较

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摘要

Reuse of controls in a nested case-control (NCC) study has not been considered feasible since the controls are matched to their respective cases. However, in the last decade or so, methods have been developed that break the matching and allow for analyses where the controls are no longer tied to their cases. These methods can be divided into two groups; weighted partial likelihood (WPL) methods and full maximum likelihood methods. The weights in the WPL can be estimated in different ways and four estimation procedures are discussed. In addition, we address modifications needed to accommodate left truncation. A full likelihood approach is also presented and we suggest an aggregation technique to decrease the computation time. Furthermore, we generalize calibration for case-cohort designs to NCC studies. We consider a competing risks situation and compare WPL, full likelihood and calibration through simulations and analyses on a real data example.
机译：由于控件与各自的案例相匹配，因此在嵌套案例对照（NCC）研究中重用控件并不可行。然而，在过去的十年左右的时间里，已经开发出了打破匹配的方法，并允许对那些不再依赖于案例的控件进行分析。这些方法可以分为两组。加权偏似然法（WPL）和完全最大似然法。 WPL中的权重可以通过不同的方式进行估算，并讨论了四种估算程序。另外，我们解决了适应左截断所需的修改。还提出了全似然方法，我们建议使用一种聚合技术来减少计算时间。此外，我们将病例组设计的校准推广到NCC研究。我们考虑了竞争风险情况，并通过对真实数据示例的仿真和分析来比较WPL，完全可能性和校准。

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