Causal inference in statistics

统计学中的因果推断

• 批准号: 203137-2012
• 负责人: Platt, Robert
• 金额: $ 0.87万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=523357
• 关键词: Causal; inference; statistics

I will continue to develop my research program on statistical methods for causal inference in epidemiology, with focus on marginal structural models propensity score. My work to date has focused on the use of the propensity score in marginal structural models (MSMs) and targeted maximum likelihood (TML) methods. The core of my current and proposed work extends these results. I will investigate the properties of various statistical learning-based methods for fitting the propensity score, in the context of MSMs and TML. Via theoretical results and simulations, I will describe the properties of the HDPS in general, and in particular for use in marginal structural models.

我将继续发展我的研究计划在流行病学因果推断的统计方法，重点是边际结构模型的倾向得分。 迄今为止，我的工作主要集中在边缘结构模型（MSM）和目标最大似然（TML）方法中的倾向得分的使用。 我目前和拟议工作的核心是扩展这些结果。 我将在MSM和TML的背景下研究各种基于统计学习的方法来拟合倾向分数的属性。 通过理论结果和模拟，我将描述一般的HDPS的属性，特别是用于边际结构模型。