Development of Econometric Models for Improved Estimation of Prevention Program B

描述(由申请人提供)：拟议项目的目的是开发和测试纠错技术，以评估以社区为基础的普遍预防方案的结果。具体的总体目标是开发分析技术，以改进对社区环境中的计划有效性的评估。首先，我们建议开发一种分析方法来解决程序有效性测试中的多个偏差来源。其次，我们将把这种新颖的方法应用于正在进行的项目实施中的数据分析。第三，我们将估计这三个误差来源对个人特征如何影响项目结果的估计的程度。拟议的项目具有创新性，它结合了现有的纠错技术，以同时调整多个偏移源。它的重要之处在于，它将通过将个人一级的分析技术与综合一级的分析技术相结合，改善对方案有效性的估计。反过来，对方案有效性的改进估计将为政策制定者和管理人员提供所需的信息，以了解人口层面的方案影响；更准确地计算方案效益；比较同一方案的不同实施；以及改进方案和招聘战略。公共卫生相关性：拟议的项目将提供更准确地估计项目效益的新方法。这将使研究人员能够计算以社区为基础的预防计划的好处是否超过了它们的财务成本。这些知识有助于政策制定者决定如何将有限的资源优先用于社会项目。

DESCRIPTION (provided by applicant): The purpose of the proposed project is to develop and test error correction techniques for evaluating outcomes of community-based universal prevention programs. The specific over-arching goal is to develop analytical techniques for improved estimation of program effectiveness in community settings. We propose, first, to develop an analytic approach to address multiple sources of bias in the testing of program effectiveness. Second, we will apply this novel approach to the analysis of data from an ongoing program implementation. Third, we will estimate the degree to which the three sources of error affect estimates of how individual characteristics impact program outcomes. The proposed project is innovative in its combining of existing error correction techniques to adjust for multiple sources of bias simultaneously. It is significant in that it will result in improved estimation of program effectiveness through the integration of individual-level with aggregate-level analytic techniques. In turn, improved estimation of program effectiveness will provide policy makers and managers the information needed to understand population-level program impact; to calculate program benefits more accurately; to compare different implementations of the same program; and to refine programming and recruitment strategies. PUBLIC HEALTH RELEVANCE: The proposed project will provide new methods of estimating program benefits with greater accuracy. This will enable researchers to calculate whether the benefits of community-based prevention programs out weight their financial costs. Such knowledge is helpful to policy makers as they decide how to prioritize limited resources for social programs.