Baek Jonggyu, Sánchez Brisa N, Sanchez-Vaznaugh Emma V
Department of Biostatistics, University of Michigan, Ann Arbor, MI, U.S.A.
Stat Med. 2014 Feb 20;33(4):662-74. doi: 10.1002/sim.5967. Epub 2013 Sep 13.
Methods for multiple informants help to estimate the marginal effect of each multiple source predictor and formally compare the strength of their association with an outcome. We extend multiple informant methods to the case of hierarchical data structures to account for within cluster correlation. We apply the proposed method to examine the relationship between features of the food environment near schools and children's body mass index z-scores (BMIz). Specifically, we compare the associations between two different features of the food environment (fast food restaurants and convenience stores) with BMIz and investigate how the association between the number of fast food restaurants or convenience stores and child's BMIz varies across distance from a school. The newly developed methodology enhances the types of research questions that can be asked by investigators studying effects of environment on childhood obesity and can be applied to other fields.
多信息源方法有助于估计每个多源预测变量的边际效应，并正式比较它们与结果之间关联的强度。我们将多信息源方法扩展到分层数据结构的情况，以考虑聚类内相关性。我们应用所提出的方法来检验学校附近食物环境特征与儿童体重指数z评分（BMIz）之间的关系。具体而言，我们比较食物环境的两种不同特征（快餐店和便利店）与BMIz之间的关联，并研究快餐店或便利店数量与儿童BMIz之间的关联如何随距学校距离的变化而变化。新开发的方法增强了研究环境对儿童肥胖影响的研究人员可以提出的研究问题类型，并且可以应用于其他领域。
