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病例对照数据的因果分析

Causal analysis of case-control data.

作者信息

Newman Stephen C

机构信息

Department of Psychiatry, Mackenzie Health Sciences Centre, University of Alberta, Edmonton, Alberta, T6G 2B7, Canada.

出版信息

Epidemiol Perspect Innov. 2006 Jan 27;3:2. doi: 10.1186/1742-5573-3-2.

Abstract

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.

摘要

在一系列论文中,罗宾斯及其同事描述了边际结构模型(MSM)中的治疗权重逆概率(IPTW)估计,这是一种基于反事实原则的纵向数据因果分析方法。这类统计技术在概念上与调查数据加权类似,不同之处在于权重是利用研究数据估计得出,而非为反映抽样设计和对外部总体的事后分层而设定。几十年前,米耶蒂宁描述了一种基于间接标准化的病例对照数据因果分析基本方法。在本文中,我们运用与MSM中IPTW估计密切相关的理念扩展了米耶蒂宁方法。通过一项关于口服避孕药与心肌梗死的病例对照研究数据对该技术进行了说明。

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