Sample size estimation for alternating logistic regressions analysis of multilevel randomized community trials of under-age drinking
Sample size estimation for alternating logistic regressions analysis of multilevel randomized community trials of under-age drinking
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DOI：
10.1111/j.1467-985x.2011.01003.x
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发表时间：
2012-01-01
影响因子：
2
通讯作者：
Wolfson, Mark
中科院分区：
文献类型：
--
作者：
Reboussin, Beth A.;Preisser, John S.;Wolfson, Mark
.在美国，未成年人饮酒是一个巨大的公共卫生问题。有证据表明，社区一级的结构可能会影响到未成年人饮酒，这导致人们越来越多地努力改变饮酒的环境。虽然这些努力的重点是减少个别青年的饮酒，但环境干预措施通常在社区一级实施，整个社区被随机分配到相同的干预条件下。这些试验的一个显著特点是，居住在同一社区的个人的行为比居住在不同社区的其他人的行为更相似，这在本文中被称为聚类。统计分析和样本量计算必须考虑这种聚类，以避免I类错误，并确保适当的把握度试验。聚类本身也可能具有科学意义。我们认为交替逻辑回归过程中的人口平均建模框架，以估计执法干预对未成年人饮酒行为的流行率的影响，同时在多个层面上建模的聚类，例如，在社区内和社区内嵌套的邻里，通过使用成对的比值比。然后，我们推导出样本量公式估计干预效果时，计划后测试，只有或重复的横断面社区随机试验使用交替逻辑回归程序。
. Under-age drinking is an enormous public health issue in the USA. Evidence that community level structures may impact on under-age drinking has led to a proliferation of efforts to change the environment surrounding the use of alcohol. Although the focus of these efforts is to reduce drinking by individual youths, environmental interventions are typically implemented at the community level with entire communities randomized to the same intervention condition. A distinct feature of these trials is the tendency of the behaviours of individuals residing in the same community to be more alike than that of others residing in different communities, which is herein called clustering. Statistical analyses and sample size calculations must account for this clustering to avoid type I errors and to ensure an appropriately powered trial. Clustering itself may also be of scientific interest. We consider the alternating logistic regressions procedure within the population-averaged modelling framework to estimate the effect of a law enforcement intervention on the prevalence of under-age drinking behaviours while modelling the clustering at multiple levels, e.g. within communities and within neighbourhoods nested within communities, by using pairwise odds ratios. We then derive sample size formulae for estimating intervention effects when planning a post-test-only or repeated cross-sectional community-randomized trial using the alternating logistic regressions procedure.