ESTIMATING MEDIATION EFFECTS IN PREVENTION STUDIES

估计预防研究中的中介效应

• 批准号: 2443500
• 负责人: David P MacKinnon
• 金额: $ 21.01万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-07-01 至 2000-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2443500
• 关键词: alcoholism /alcohol abuse prevention; androgen analog; behavioral /social science research tag; computer assisted instruction; drug abuse prevention; health care service evaluation; human data; human therapy evaluation; mathematical model; method development; outcomes research; statistics /biometry; stress management

DESCRIPTION: (Applicant's Abstract) The purpose of this proposal is to develop 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 outcomes. As noted by many researchers, mediation analyses identify the most effective program components and increase understanding of the underlying processes leading to-drug use. The need for these new procedures became apparent in the analyses of several NIDA funded drug prevention programs. The P.I. of this grant received a one-year NIDA small grant to study the assessment of mediation effects. In this proposal, we request four years of funding to develop methods and statistical procedures for the more complicated types of designs and procedures commonly used in prevention research. In the first of seven proposed studies, we examine type 1 error and statistical power of tests of mediation. In Study 2, mediated effects in multiple mediator and longitudinal models are examined. In Study 3, we develop and evaluate methods to estimate mediated effects in the nonequivalent control group design. In Study 4, we develop and evaluate methods to estimate mediated effects in logistic regression and the proportional hazards model. In Study 5, we develop and evaluate methods to estimate mediation effects in a variety of designs, including the hierarchical regression model and models with both moderator and mediator effects. In Study 6, we examine the effects of missing data, measurement error, non-normal data, and outliers on the estimation of mediated effects. In Study 7, we apply the new methods in several NIDA funded drug prevention projects. As part of Study 7, we will increase the use of mediation methods by the establishment of a consultation service and an interactive computer program to teach researchers how to conduct mediation analysis.

描述：（申请人摘要） 这项建议的目的是制定方法和统计 确定预防计划如何改变结果变量的程序。 这些中介分析评估了项目对 预防计划针对的结构和对结果的影响。 作为 许多研究人员指出，调解分析确定了最有效的 程序组件，并增加对底层过程的理解 导致吸毒 在对几个国家的分析中，这些新程序的必要性变得显而易见。 NIDA资助的药物预防计划。 私家侦探其中，A 一年NIDA小额赠款，研究评估调解效果。 在 根据这项建议，我们要求四年的资金来制定方法， 更复杂的设计类型的统计程序， 预防研究中常用的方法。 在第一个七 提出的研究，我们检查1型错误和统计检验的权力， 调解 在研究2中，在多个介质和 纵向模型进行了研究。 在研究3中，我们开发并评估了 估计不等效对照组中介导效应的方法 设计 在研究4中，我们开发并评估了估计介导的 Logistic回归和比例风险模型的影响。 在自习 5，我们开发和评估方法，以估计调解效果， 各种设计，包括分层回归模型和模型 具有调节和中介效应。 在研究6中，我们检查了 缺失数据、测量误差、非正态数据和离群值对 中介效应的估计。 在研究7中，我们将新方法应用于 NIDA资助的几个毒品预防项目。 作为研究7的一部分，我们将 通过建立协商机制， 服务和一个交互式计算机程序，教研究人员如何 进行调解分析。