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Causal inference in statistics

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:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2014
资助国家:
加拿大
项目状态:
已结题
起止时间:
2014-01-01 至 2015-12-31

项目摘要

项目成果

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中文摘要
翻译
我将继续发展我的流行病学因果推断统计方法的研究计划,重点放在边缘结构模型倾向评分上。到目前为止,我的工作主要集中在边际结构模型(MSM)和目标最大似然(TML)方法中倾向评分的使用。我当前和提议的工作的核心是对这些结果的扩展。我将在MSMS和TML的背景下,研究各种基于统计学习的方法来拟合倾向性分数的特性。通过理论结果和模拟,我将描述HDPS的一般性质,特别是用于边缘结构模型的性质。
英文摘要
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.
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Statistical Methods for High-Dimensional Administrative Data
  • 批准号:
    RGPIN-2017-04363
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.37万
  • 财政年份:
    2021
  • 负责人:
    Platt, Robert
  • 依托单位:
Statistical Methods for High-Dimensional Administrative Data
  • 批准号:
    RGPIN-2017-04363
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.19万
  • 财政年份:
    2020
  • 负责人:
    Platt, Robert
  • 依托单位:
Statistical Methods for High-Dimensional Administrative Data
  • 批准号:
    RGPIN-2017-04363
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.19万
  • 财政年份:
    2019
  • 负责人:
    Platt, Robert
  • 依托单位:
Statistical Methods for High-Dimensional Administrative Data
  • 批准号:
    RGPIN-2017-04363
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.19万
  • 财政年份:
    2018
  • 负责人:
    Platt, Robert
  • 依托单位:
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