Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, 43210, U.S.A.
Stat Med. 2014 Jun 15;33(13):2178-90. doi: 10.1002/sim.6083. Epub 2014 Jan 8.
Participants in trials may be randomized either individually or in groups and may receive their treatment either entirely individually, entirely in groups, or partially individually and partially in groups. This paper concerns cases in which participants receive their treatment either entirely or partially in groups, regardless of how they were randomized. Participants in group-randomized trials are randomized in groups, and participants in individually randomized group treatment trials are individually randomized, but participants in both types of trials receive part or all of their treatment in groups or through common change agents. Participants who receive part or all of their treatment in a group are expected to have positively correlated outcome measurements. This paper addresses a situation that occurs in group-randomized trials and individually randomized group treatment trials-participants receive treatment through more than one group. As motivation, we consider trials in The Childhood Obesity Prevention and Treatment Research Consortium, in which each child participant receives treatment in at least two groups. In simulation studies, we considered several possible analytic approaches over a variety of possible group structures. A mixed model with random effects for both groups provided the only consistent protection against inflated type I error rates and did so at the cost of only moderate loss of power when intraclass correlations were not large. We recommend constraining variance estimates to be positive and using the Kenward-Roger adjustment for degrees of freedom; this combination provided additional power but maintained type I error rates at the nominal level.
参与者可以个体或群体随机分组，并且可以接受完全个体治疗、完全群体治疗或部分个体和部分群体治疗。本文关注的是无论参与者如何随机分组，他们都接受完全或部分群体治疗的情况。群体随机试验中的参与者是按群体随机分组的，个体随机分组治疗试验中的参与者是个体随机分组的，但这两种类型的试验中的参与者都通过共同的改变因素接受部分或全部群体治疗。接受部分或全部群体治疗的参与者的结果测量预计会存在正相关。本文解决了群体随机试验和个体随机分组治疗试验中出现的一种情况——参与者通过多个群体接受治疗。作为动机，我们考虑了“儿童肥胖预防和治疗研究联盟”中的试验，每个儿童参与者都在至少两个组中接受治疗。在模拟研究中，我们考虑了多种可能的群体结构下的几种可能的分析方法。对于组间随机效应的混合模型提供了唯一的一致保护，防止了 I 型错误率膨胀，并且在组内相关系数不大时，仅以适度的损失功效为代价。我们建议将方差估计约束为正，并使用肯沃德-罗杰自由度调整；这种组合提供了额外的功效，但将 I 型错误率保持在名义水平。
