Rivera C L, Lumley T
Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Kresge 803B, Boston, MA 02115, U.S.A.
Stat Med. 2016 Aug 15;35(18):3213-28. doi: 10.1002/sim.6917. Epub 2016 Feb 22.
Countermatching designs can provide more efficient estimates than simple matching or case-cohort designs in certain situations such as when good surrogate variables for an exposure of interest are available. We extend pseudolikelihood estimation for the Cox model under countermatching designs to models where time-varying covariates are considered. We also implement pseudolikelihood with calibrated weights to improve efficiency in nested case-control designs in the presence of time-varying variables. A simulation study is carried out, which considers four different scenarios including a binary time-dependent variable, a continuous time-dependent variable, and the case including interactions in each. Simulation results show that pseudolikelihood with calibrated weights under countermatching offers large gains in efficiency if compared to case-cohort. Pseudolikelihood with calibrated weights yielded more efficient estimators than pseudolikelihood estimators. Additionally, estimators were more efficient under countermatching than under case-cohort for the situations considered. The methods are illustrated using the Colorado Plateau uranium miners cohort. Furthermore, we present a general method to generate survival times with time-varying covariates. Copyright © 2016 John Wiley & Sons, Ltd.
在某些情况下，比如当存在感兴趣暴露的良好替代变量时，配对设计能够比简单匹配或病例队列设计提供更有效的估计。我们将配对设计下Cox模型的拟似然估计扩展到考虑时变协变量的模型。我们还实施了带有校准权重的拟似然估计，以在存在时变变量的嵌套病例对照设计中提高效率。开展了一项模拟研究，该研究考虑了四种不同的情形，包括一个二元时依变量、一个连续时依变量，以及每种情形中包含交互作用的情况。模拟结果表明，与病例队列相比，配对设计下带有校准权重的拟似然估计在效率上有很大提升。带有校准权重的拟似然估计比拟似然估计产生了更有效的估计量。此外，在所考虑的情形下，配对设计下的估计量比病例队列设计下的估计量更有效。使用科罗拉多高原铀矿矿工队列对这些方法进行了说明。此外，我们提出了一种生成具有时变协变量生存时间的通用方法。版权所有© 2016约翰威立父子有限公司。
