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Causal analysis of case-control data

机译:病例对照数据的因果分析

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In a series of papers, Robins and colleagues describe inverse probability of treatment weighted (IPTW) estimation in marginal structural models (MSMs), a method of causal analysis of longitudinal data based on counterfactual principles. This family of statistical techniques is similar in concept to weighting of survey data, except that the weights are estimated using study data rather than defined so as to reflect sampling design and post-stratification to an external population. Several decades ago Miettinen described an elementary method of causal analysis of case-control data based on indirect standardization. In this paper we extend the Miettinen approach using ideas closely related to IPTW estimation in MSMs. The technique is illustrated using data from a case-control study of oral contraceptives and myocardial infarction.
机译:在一系列论文中,Robins及其同事在边缘结构模型(MSM)中描述了治疗加权加权逆估计(IPTW),这是一种基于反事实原理的纵向数据的因果分析方法。该统计技术系列在概念上与调查数据的加权类似,不同的是,加权是使用研究数据估算的,而不是为了反映抽样设计和对外部人群的后分层而定义的。几十年前,Miettinen描述了一种基于间接标准化的案例控制数据因果分析的基本方法。在本文中,我们使用与MSM中IPTW估计紧密相关的思想扩展了Miettinen方法。使用口服避孕药和心肌梗塞病例对照研究的数据说明了该技术。

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