病例对照资料的因果分析。

Stephen C Newman
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引用次数: 0

摘要

在一系列论文中,Robins及其同事描述了边际结构模型(MSM)中的处理加权逆概率(IPTW)估计,这是一种基于反事实原理的纵向数据因果分析方法。这一系列统计技术在概念上与调查数据的权重相似,只是权重是使用研究数据估计的,而不是定义的,以反映抽样设计和对外部人群的后分层。几十年前,Miettinen描述了一种基于间接标准化的病例对照数据因果分析的基本方法。在本文中,我们使用与MSM中的IPTW估计密切相关的思想来扩展Miettinen方法。这项技术是用来自口服避孕药和心肌梗死病例对照研究的数据来说明的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Causal analysis of case-control data.

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.

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