Risk in Context: New Methodology for Modeling Risk by Context Interactions

这笔赠款将审查新的统计方法的使用，以更好地识别受访者群体 他们在环境(家庭、学校和社区)对结果的影响方面存在差异。助学金 重点介绍回归混合模型的使用，该模型具有识别 受试者基于预测因素与结果的关系。这项工作的重点是使用这些 在使用真实数据评估上下文影响时遇到的条件下的方法。 具体地说，我们的目标是：1)测试验证回归混合结果的新方法；2) 检查使用回归混合来评估复杂的适度，其中许多上下文 变量汇聚在一起会产生不同的影响；以及3)测试回归混合的使用 评估多层次的上下文影响，包括制定一套使用 这些方法。这些目标将通过使用蒙特卡罗模拟以及 具有三个真实数据集的应用程序查看家庭、学校和社区对 身体活动、成就和社交技能，以及抑郁症的发展。这笔赠款的目的是 为了为更好地发现差异效应提供基础，开发的工具将允许更好地 对环境背景的影响的差异的理解，这些环境背景预期将提供信息 努力预防和治疗健康问题。

This grant will examine the use of new statistical methods for better identifying groups of respondents who differ in the effects of contexts (families, schools, and communities) on outcomes. The grant focuses on the use of regression mixture models, which have the unique ability to identify groups of subjects based on the relationship of predictors with outcomes. This work focuses on the use of these methods under conditions encountered when assessing the effects of contexts with real data. Specifically, we aim to: 1) test new methods for validating the results of regression mixtures; 2) examine the use of regression mixtures for assessing complex moderation where many contextual variables come together to cause differential effects; and 3) test the use of regression mixtures for assessing multilevel contextual effects, including developing a set of best practices for the use of these methods. These aims will be investigated through the use of Monte Carlo simulations as well as applications with three real datasets looking at the effects of families, schools, and communities on physical activity, achievement and social skills, and the development of depression. This grant aims to provide a basis for better finding differential effects, the tools developed will allow for better understanding of differences in the effects of environmental contexts which are expected to inform efforts to prevent and treat health problems.