NOSI to Support Enhancement of Software Tools for Multilevel Mediation Analysis for Investigating Effects of Environmental and Individual Risk Factors on Respiratory Diseases

环境和个人影响调查的多水平中介分析 呼吸系统疾病的危险因素 暴露在颗粒物(PM)和不良的呼吸道健康之间有很好的联系 已经成立了。通过项目1的目标3，路易斯安那州立大学超级基金研究中心假设 来自危险废物场地的环境持久性自由基(EPFR)， 焚烧炉/化学火灾和其他来源是PM之间缺失的机械联系 暴露和呼吸健康状况不佳。我们将调查该协会的调解使用 层次化中介分析将大气污染物对呼吸道的不良影响分解为 直接和间接(EPFR介导的)影响。 我们开发了一种多层次的中介分析方法，允许纵向 共同利用的居住环境和个人风险因素评估 确定暴露在PM和呼吸健康不良之间的机械联系。通过 包括对个体行为因素的衡量，我们的方法能够解释 在健康结果方面存在差异。 我们以R包(MLMA)的形式实现了我们的方法，以向研究社区提供 开放访问用于执行多级分层调解分析的软件。然而， 使用我们的R包确实需要了解R，这限制了它在研究中的更广泛使用。至 针对这一限制，我们建议与路易斯安那州立大学的一名软件工程师合作，创建一个 用于我们的调解软件的交互式Web实施的API。我们预计这将是 极大地扩展了对我们方法的访问，因为不需要编程。拟议中的应用程序， 凭借其直观的交互式可视化界面，将允许用户轻松读取数据集并构建 使用拖放功能的概念性调解模型框架。我们还将提供 图形工具，如有向无环图，允许用户直观地解释分析 结果。此外，我们还将把部分计算转换为高效的低级计算机 语言，以提高计算速度，并计划使用云计算资源，使R 和相关联的软件包不必安装在单独的计算机上 执行分析。

Multilevel Mediation Analysis for Investigating Effects of Environmental and Individual Risk Factors on Respiratory Diseases The link between particulate matter (PM) exposure and poor respiratory health is well established. Through Aim 3 of Project 1, the LSU Superfund Research Center postulates that environmentally persistent free radicals (EPFRs) from hazardous waste sites, incinerators/chemical fires, and other sources is the missing mechanistic link between PM exposure and poor respiratory health. We will investigate the mediation of this association using hierarchical mediation analysis to decompose the air pollutant adverse respiratory effects into direct and indirect (EPFR-mediated) effects. We developed a multilevel mediation analysis method that allows for both longitudinal assessments of residential environments and individual risk factors to be jointly utilized in determining the mechanistic link between exposure to PM and poor respiratory health. By including measures of individual behavioral factors our methods are capable of explaining existing disparities in health outcomes. We have implemented our method as an R package (mlma) to provide the research community with open access to software for performing multilevel hierarchical mediation analysis. However, use of our R package does require knowledge of R, which limits its broader use in research. To address this limitation, we propose to collaborate with a software engineer at LSU to create an API for an interactive web implementation of our mediation software. We expect that this would greatly expand access to our methods, as no programming will be required. The proposed app, with its intuitive interactive visual interface, will allow users to easily read in datasets and build a conceptual mediation model framework using drag-and-drop functionality. We will also provide graphical tools such as directed acyclic graphs to allow users to visually interpret the analysis results. In addition, we will transform part of the computing to an efficient low-level computer language to improve computational speed and plan to use cloud computing resources so that R and associated software packages do not have to be installed on individual computers to perform the analysis.