Multilevel latent class and social network models for observational adolescent ob

描述（由申请人提供）：青少年肥胖现在被认为具有复杂的病因。生态模型经常被用来解释这种复杂性，在个人、家庭、同伴、学校和社区层面上有不同程度的影响。不仅存在多个层次的影响，而且这些不同层次之间的影响关系是双向的，这进一步增加了复杂性。虽然生态框架通常用于从概念上解释肥胖，但很少有统计测试这种多层次模型的例子。本提案将开发和研究新的统计模型和方法，其中包括潜在变量、社会网络和倾向分数，这些模型和方法同时包含来自对青少年肥胖的多层次影响的多个变量，以便对这一现象有更丰富的理解。将利用对种族和社会经济状况不同的青少年进行的大规模人口纵向和连续横断面调查（EAT项目）所得的现有数据，为这些青少年制定在计算上可行的统计模型和适当的估计方法。除了广泛的个人水平问卷数据和用于计算BMI的测量身高和体重外，青少年还提供了提供同伴网络信息的提名朋友名单。这些数据都是在学校收集的。此外，收集了学校环境和政策数据以及青少年的居住社区信息。EAT项目的数据来源提供了丰富的内容，新的、更完整的层次模型可以用来建立我们对青少年肥胖的理解。所提出的分析都不是EAT项目原始分析计划的一部分，每一个分析都代表了我们在已经完成的基础上更进一步的尝试。

DESCRIPTION (provided by applicant): Adolescent obesity is now recognized as having a complex etiology. Ecological models are often used to explain this complexity, with different levels of influence at the individual, familial, peer, school, and neighborhood levels. Not only are there multiple levels of influence, but these different levels have bidirectional relationships of influence between them, further adding to the complexity. While the ecological framework is often used to conceptually explain obesity, there are few examples of statistically testing this type of multilevel model. This proposal will develop and examine new statistical models and methods incorporating latent variables, social networks and propensity scores that simultaneously incorporate multiple variables from multilevels of influence on adolescent obesity in order to inform a richer understanding of the phenomena. Using existing data from a large population-based longitudinal and serial cross-sectional survey of ethnically and socioeconomically diverse adolescents (Project EAT), statistical models and appropriate estimation methods for them which are computationally feasible will be developed. In addition to extensive individual level questionnaire data and measured heights and weights used to calculate BMI, adolescents also provide lists of nominated friends providing information about peer-networks. These data are all collected at school. Furthermore, school environmental and policy data are collected as well as the adolescent's residential neighborhood information. The Project EAT data source provides the richness that new, more completely developed hierarchical models could exploit in building our understanding about adolescent obesity. None of the analyses being proposed were part of the original analysis plan of Project EAT and each represents our attempt to go a step beyond what has been done.