Evaluating group-based interventions when control participants are ungrouped
Evaluating group-based interventions when control participants are ungrouped
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DOI：
10.1080/00273170802034810
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发表时间：
2008-04-01
影响因子：
3.8
通讯作者：
Hallfors, Denise Dion
中科院分区：
文献类型：
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作者：
Bauer, Daniel J.;Sterba, Sonya K.;Hallfors, Denise Dion
单独随机的治疗通常在小组环境中进行。因此，由于提供者效应、群体内的共同经历和/或非正式的社会化过程，接受治疗的个人的结果可能是相关的。相反，考虑到对照参与者没有被归入小组，通常认为这些人的结果是独立的是合理的。虽然这种设计在干预研究中很常见，但用于评估治疗效果的统计模型通常与结果数据结构不一致，可能导致偏颇的推断。这篇文章提出了一个替代模型，该模型明确地解释了只有接受治疗的参与者被分组的事实。除了提供对总体治疗效果的有用测试外，这种方法还允许人们正式确定治疗效果在不同治疗组之间的差异程度，以及是否有证据表明治疗组内的个人变得彼此相似。这一策略通过针对有学习失败和行为障碍风险的高中生的重新连接青年计划的数据进行了演示。
Individually randomized treatments are often administered within a group setting. As a consequence, outcomes for treated individuals may be correlated due to provider effects, common experiences within the group, and/or informal processes of socialization. In contrast, it is often reasonable to regard outcomes for control participants as independent, given that these individuals are not placed into groups. Although this kind of design is common in intervention research, the statistical models applied to evaluate the treatment effects are usually inconsistent with the resulting data structure, potentially leading to biased inferences. This article presents an alternative model that explicitly accounts for the fact that only treated participants are grouped. In addition to providing a useful test of the overall treatment effect, this approach also permits one to formally determine the extent to which treatment effects vary over treatment groups and whether there is evidence that individuals within treatment groups become similar to one another. This strategy is demonstrated with data from the Reconnecting Youth program for high school students at risk of school failure and behavioral disorders.