Statistical Methods for Causal Inference

因果推断的统计方法

• 批准号: MC_UU_00032/2
• 负责人: Kate Tilling
• 金额: $ 198.01万
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MC_UU_00032%2F2
• 关键词: Statistical; Methods; Causal; Inference

Working out which treatments or interventions are effective, using only observational data, needs increasingly sophisticated statistical methods. We aim to develop methods to enable researchers to estimate the effects of interventions as accurately as possible.We will develop models to help identify those who would benefit most from a given intervention, so enabling better targeting of treatments. Most measures in observational data are made with some error (e.g. blood pressure varies throughout the day) and we will extend current methods to reduce the effect this has on causal estimates. We will also develop ways to use current methods based on mendelian randomization (MR) to improve analyses of non-genetic exposures, such as examining the benefits of cycling to work. Current methods tend to focus on one intervention, and we will extend these to examine the long-term effects, for example to assess the impact of remaining heavier than average throughout adolescence and adulthood vs losing weight during adulthood. Finally, we will improve methods for combining evidence from several different study types to answer the same question, by developing a triangulation framework.

仅使用观察数据来确定哪些治疗或干预措施有效，需要日益复杂的统计方法。我们的目标是开发方法，使研究人员能够尽可能准确地估计干预措施的效果。我们将开发模型来帮助确定哪些人将从特定干预措施中受益最大，从而更好地制定治疗目标。观察数据中的大多数测量都存在一些误差（例如血压全天变化），我们将扩展当前的方法以减少这对因果估计的影响。我们还将开发使用基于孟德尔随机化 (MR) 的现有方法来改进对非遗传暴露的分析，例如检查骑自行车上班的好处。目前的方法往往侧重于一种干预措施，我们将扩展这些干预措施以检查长期影响，例如评估在整个青春期和成年期保持体重高于平均水平与在成年期减肥的影响。最后，我们将通过开发三角测量框架来改进结合多种不同研究类型的证据来回答同一问题的方法。

项目成果

Two sample Mendelian Randomisation using an outcome from a multilevel model of disease progression

• DOI: 10.1007/s10654-023-01093-2
• 发表时间: 2023-05
• 期刊: European Journal of Epidemiology
• 影响因子: 13.6
• 作者: M. Lawton;Y. Ben-Shlomo;A. Gkatzionis;Michele T M Hu;D. Grosset;K. Tilling

Investigation of genetic determinants of cognitive change in later life.

• DOI: 10.1038/s41398-023-02726-6
• 发表时间: 2024-01-18
• 期刊: TRANSLATIONAL PSYCHIATRY
• 影响因子: 6.8
• 作者: Mahedy, Liam;Anderson, Emma L.;Tilling, Kate;Thornton, Zak A.;Elmore, Andrew R.;Szalma, Sandor;Simen, Arthur;Culp, Meredith;Zicha, Stephen;Harel, Brian T.;Davey Smith, George;Smith, Erin N.;Paternoster, Lavinia
• 通讯作者: Paternoster, Lavinia