Statistical methods for modelling the pathways between cause and effect

因果关系建模的统计方法

• 批准号: DE190101326
• 负责人: A/Prof Margarita Moreno-Betancur
• 金额: $ 27.51万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2019
• 资助国家: 澳大利亚
• 起止时间: 2019-04-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE190101326
• 关键词: Statistical; methods; modelling; pathways; between

This project aims to develop new biostatistical methods for addressing complex analytic questions that arise in studies of the causes of health, social, educational and other outcomes in the course of human life. These questions concern the pathways that explain how intermediate factors contribute to a statistical relationship between a probable cause of a later outcome. Mathematical and statistical innovation is needed to address them. The expected outcomes include a suite of novel methods designed to evaluate the impact of intervening to modify causal pathways, while also accommodating common complexities of data such as incompleteness. This project should provide major benefits to studies in public health, social sciences and economics.

该项目旨在开发新的生物统计方法，以解决人类生命过程中健康、社会、教育和其他结果的原因研究中出现的复杂分析问题。这些问题涉及解释中间因素如何影响后来结果的可能原因之间的统计关系的途径。需要数学和统计创新来解决这些问题。预期结果包括一套新颖的方法，旨在评估干预措施修改因果路径的影响，同时也适应数据的常见复杂性，例如不完整性。该项目将为公共卫生、社会科学和经济学研究带来重大益处。