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。具体的过度研究目标是开发分析技术，以改善社区环境中的计划有效性的估计。我们建议，首先，开发一种分析方法，以解决多种来源的偏见在测试程序的有效性。其次，我们将应用这种新的方法来分析正在进行的计划实施的数据。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影响程度。拟议的项目是创新的结合现有的纠错技术，以调整多个来源的偏见同时进行。它的重要性在于，它将导致通过集成的个人层面与总体层面的分析技术，以改善评估程序的有效性。反过来，改进对方案有效性的估计将为决策者和管理人员提供了解人口一级方案影响所需的信息;更准确地计算方案效益;比较同一方案的不同实施情况;以及改进方案拟订和征聘战略。公共卫生相关性：拟议的项目将提供更准确地估计计划效益的新方法。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其财务成本。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方案。

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.