Collaborative Research: Power Analyses for Moderator and Mediator Effects in Cluster Randomized Trials

协作研究：集群随机试验中调节剂和中介效应的功效分析

• 批准号: 1437745
• 负责人: Nianbo Dong
• 金额: $ 24.36万
• 依托单位: University of Missouri-Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-15 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1437745&HistoricalAwards=false
• 关键词: Collaborative; Research; Power; Analyses; Moderator

Cluster randomized experiments are considered the gold standards by which the impact of educational treatments and interventions can be determined. One of the most important design decisions that must be made is determining the size of the sample of classrooms or teachers or schools that must be studied in order to determine a statistically significant effect of the treatment on the outcomes under study. However, currently it is common for a cluster randomized trial to be designed to detect only the main effect of a treatment with adequate power. These studies miss out on being able to provide valid assessments of for whom a treatment might have an impact (mediation) and the conditions under which a treatment is effective (moderation). This study will advance our understanding of cluster randomized trials by developing power formulas and software for tests of multi-level moderation and mediation, as well as the combination of the two.This project will have three components as follows: 1). development of new formulas for estimating the statistical power to deter multilevel moderation, mediation, moderated-mediation and mediated-moderation in cluster randomized trials; 2). assess and validate the formulas through simulations; and, 3). Implement the formulas in two existing software programs, Optimal Design Plus and PowerUp!. The project will develop training materials for the use of the new analyses and develop and conduct workshops in order to disseminate the tool widely to the field.

集群随机实验被认为是黄金标准，通过它可以确定教育治疗和干预的影响。必须做出的最重要的设计决定之一是确定必须研究的教室或教师或学校的样本规模，以确定治疗对研究结果的统计学显著影响。然而，目前通常的情况是，设计成簇随机试验仅检测具有足够把握度的治疗的主要效应。这些研究错过了能够提供有效评估的治疗可能会产生影响（调解）和治疗有效的条件（适度）。本研究将通过开发多水平调节和中介检验的功效公式和软件，以及多水平调节和中介检验与多水平中介检验相结合的方法，来提高我们对整群随机试验的理解。发展新的公式估计统计权力，以阻止多层次的调解，调解，调解和调解在集群随机试验; 2）。通过模拟评估和验证公式; 3）.在两个现有的软件程序Optimal Design Plus和PowerUp！中实现公式。该项目将开发使用新分析的培训材料，并开发和举办研讨会，以便向实地广泛传播该工具。