Estimating Mediation Effects in Prevention Studies

摘要 这一竞争性继续补助金提案的目的是继续开发、评估和 应用方法学和统计学程序来确定预防计划如何改变结果 变量这些中介分析评估了项目对目标结构的影响之间的联系， 预防措施及效果。正如许多研究人员所指出的，调解分析确定了 最有效的计划组成部分，并增加对潜在过程的理解， 改变结果变量。 私家侦探。这笔赠款中有一笔是一年期的NIDA小额赠款，另一笔是两笔四年期赠款， 评估中介分析方法和统计程序的设计和程序共同 用于预防研究。拟议的五年延续研究集中于以下方面的实际需要： 研究人员，将最近的统计发展应用于调解分析，并为新的 预防研究设计。四个统计主题代表了本研究的下一步，包括 分析和模拟研究以及实际病因学和预防数据的应用。在研究1中， 在显着性检验的实际问题进行了调查，包括最好的方法，研究有限 样本量和评估任何调解设计所需样本量的一般方法。研究2开发 评估违反调解模型假设如何导致错误结论的方法。研究 2将因果推理的新发展扩展到中介分析，以调查和测试 调解分析。研究3开发并评估了超越潜在增长的纵向调解方法 曲线建模研究在以前的资金。调解分析的概念和统计备选办法 将彻底研究来自两个波和三个或更多波的数据。新的替代纵向 基于自回归、潜差和指数衰减微分方程的中介模型 模型将被开发和比较。研究4评估了我们先前研究中开发的一般模型， 调查调解时，也有主持人的影响或程序的影响，不同的小组， 参与者调节效应在预防研究中很常见。这项研究还将纳入纵向 一般调解和适度模型中的关系，以及调查常见的影响类型， 预防科学。研究5将统计方法应用于几个NIH资助的预防数据 提供关于模型有用性的重要反馈的集合。研究6传播新信息 通过我们的网站、与研究人员的交流以及来自 项目

Abstract The purpose of this competing continuation grant proposal is to continue developing, evaluating and applying methodological and statistical procedures to determine how prevention programs change outcome variables. These mediation analyses assess the link between program effects on the constructs targeted by a prevention program and effects on the outcome. As noted by many researchers, mediation analyses identify the most effective program components and increase understanding of the underlying processes leading to changing outcome variables. The P. I. of this grant received a one-year NIDA small grant and two four-year grants to develop and evaluate mediation analysis methods and statistical procedures for the designs and procedures commonly used in prevention research. The proposed five-year continuation study focuses on practical needs of researchers, applying recent statistical developments to mediation analysis, and developing methods for new prevention research designs. Four statistical topics represent the next steps in this research and will include analytical and simulation research as well as applications to actual etiological and prevention data. In Study 1, practical issues in significance testing are investigated including the best methods for studies with limited sample size and general methods to assess required sample size for any mediation design. Study 2 develops methods to assess how violations of assumptions of the mediation model lead to incorrect conclusions. Study 2 extends new developments in causal inference to mediation analysis to investigate and test assumptions of mediation analysis. Study 3 develops and evaluates longitudinal mediation methods beyond the latent growth curve modeling investigated in prior funding. Conceptual and statistical alternatives for mediation analysis of data from two waves and three or more waves will be thoroughly investigated. New alternative longitudinal mediation models based on autoregressive, latent difference, and exponential decay differential equation models will be developed and compared. Study 4 evaluates a general model developed in our prior research to investigate mediation when there are also moderator effects or program effects that differ by subgroups of participants. Moderator effects are common in prevention research. This study will also incorporate longitudinal relations in the general mediation and moderation model as well as investigate the types of effects common in prevention science. Study 5 applies the statistical methods to data from several NIH funded prevention data sets providing important feedback about the usefulness of the models. Study 6 disseminates new information about mediation analysis through our website, by communication with researchers, and publications from the project.