Bayesian Analysis of Treatment Effects in Experiments with Imperfect Compliance

不完美依从性实验中治疗效果的贝叶斯分析

• 批准号: DP0880069
• 负责人: A/Prof Liana Jacobi
• 金额: $ 4.56万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2008
• 资助国家: 澳大利亚
• 起止时间: 2008-02-19 至 2013-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0880069
• 关键词: Bayesian; Analysis; Treatment; Effects; Experiments

This research has a potential to benefit society by providing methods to evaluate the effectiveness of medical treatments and socio-economic and health related interventions and policies based on experiments with imperfect compliance. The proposed methods are directly relevant to the second national research priority, as they can be used to test potential measures for preventative health care and to evaluate measures for strengthening Australia's social and economic fabric. The usefulness of our methods is demonstrated in the analysis of the effectiveness of a training program for the unemployed in alleviating negative mental health effects from job loss.

这项研究有可能造福社会，提供方法来评估医疗和社会经济和健康相关的干预措施和政策的有效性的基础上，不完善的遵守实验。所提出的方法与第二个国家研究重点直接相关，因为它们可用于测试预防性保健的潜在措施，并评估加强澳大利亚社会和经济结构的措施。我们的方法的有用性证明了在分析的有效性的培训计划的失业者在减轻心理健康的负面影响，从失业。