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Subject-level matching for imbalance in cluster randomized trials with a small number of clusters

机译:具有少量聚类的聚类随机试验中受试者水平的失衡匹配

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In a cluster randomized controlled trial (RCT), the number of randomized units is typically considerably smaller than in trials where the unit of randomization is the patient. If the number of randomized clusters is small, there is a reasonable chance of baseline imbalance between the experimental and control groups. This imbalance threatens the validity of inferences regarding post-treatment intervention effects unless an appropriate statistical adjustment is used. Here, we consider application of the propensity score adjustment for cluster RCTs. For the purpose of illustration, we apply the propensity adjustment to a cluster RCT that evaluated an intervention to reduce suicidal ideation and depression. This approach to adjusting imbalance had considerable bearing on the interpretation of results. A simulation study demonstrates that the propensity adjustment reduced well over 90% of the bias seen in unadjusted models for the specifications examined.
机译:在整群随机对照试验(RCT)中,随机单位的数量通常比以患者为随机单位的试验小得多。如果随机簇的数量较少,则实验组和对照组之间存在基线不平衡的合理机会。除非使用适当的统计调整,否则这种失衡威胁了有关治疗后干预效果的推论的有效性。在这里,我们考虑将倾向得分调整应用于集群RCT。出于说明目的,我们将倾向性调整应用于评估了减少自杀意念和抑郁的干预措施的集群RCT。这种调整失衡的方法对结果的解释有很大影响。仿真研究表明,对于所检查的规格,倾向性调整可将未调整模型中的偏差减少90%以上。

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