School of Nursing, Medicine and Public Health, Clinical Science Center, University of Wisconsin-Madison, H6/273, 600 Highland Avenue, Madison, WI 53792-2455.
Res Nurs Health. 2013 Apr;36(2):216-23. doi: 10.1002/nur.21523. Epub 2013 Jan 15.
Cluster randomized controlled trials (CRCT) can be susceptible to a wide range of methodological problems. Many of these problems are not commonly recognized by researchers. This article is focused on one potential problem, the issue of impure clustering (multiple patient membership) within the CRCT structures and how it can lead to possible misunderstanding and bias in the results of the trial. A solution to this problem is presented using a multiple membership random effects model (MMREM). A simulated example of a three-level CRCT is presented and modeled with and without multiple patient membership data. Results indicate underestimation of higher level variances, and overestimation of lower-level variances, while also indicating underestimation of level predictors where the multiple membership occurs.
群组随机对照试验（CRCT）可能容易受到多种方法学问题的影响。其中许多问题并未得到研究人员的普遍认识。本文主要关注一个潜在问题，即 CRCT 结构中存在的不纯聚类（多个患者成员）问题，以及它如何导致试验结果可能产生误解和偏差。本文使用多成员随机效应模型（MMREM）提出了解决该问题的方法。本文还提出了一个三级 CRCT 的模拟示例，并分别对包含和不包含多成员数据的情况进行了建模。结果表明，当存在多成员数据时，会低估高层方差，高估低层方差，同时也会低估发生多成员数据的层次预测因子。
