Department of Biostatistics, Georgia Health Sciences University, 112015th Street, AE-1014 Augusta, GA 30912, USA.
Stat Med. 2012 Nov 30;31(27):3299-312. doi: 10.1002/sim.5355. Epub 2012 Aug 3.
Paired data from matched case-control studies are commonly used to estimate the association between the exposure to a risk factor and the occurrence of a disease. The odds ratio is typically used to quantify this association. Difficulties in estimating the true odds ratio with matched pairs arise, however, when the exposure status is unknown for one of the individuals in one or more pairs. In this article, we propose a simple method for estimating the odds ratio when the sample consists of a combination of complete and incomplete matched pairs; that is, some of the pairs have exposure data for both the case and the control, some of the pairs have exposure data just for the case, and the remaining pairs have exposure data just for the control. This method uses a weighted average of the odds ratio estimator that is most commonly used when the sample consists entirely of complete paired observations and the odds ratio estimator that is most commonly used when the sample consists entirely of unpaired observations. The proposed estimator has simple closed-form expressions for the estimate of the odds ratio and its approximate variance. We compare our method to existing methods via simulation and show that our method is comparable to or better than the other methods in terms of bias, mean squared error, and confidence interval coverage probability and width.
配对病例对照研究中的配对数据通常用于估计暴露于危险因素与疾病发生之间的关联。比值比通常用于量化这种关联。然而，当一个或多个配对中的一个个体的暴露状态未知时，估计真实比值比会遇到困难。在本文中，我们提出了一种简单的方法来估计当样本由完全和不完全配对组合组成时的比值比；也就是说，一些配对既有病例的暴露数据，也有对照的暴露数据，一些配对只有病例的暴露数据，其余的配对只有对照的暴露数据。该方法使用最常用于完全配对观察样本的比值比估计量和最常用于完全非配对观察样本的比值比估计量的加权平均值。所提出的估计量具有比值比的估计值及其近似方差的简单闭式表达式。我们通过模拟将我们的方法与现有方法进行了比较，结果表明，在偏差、均方误差以及置信区间覆盖率和宽度方面，我们的方法与其他方法相当或更好。
