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Testing for causality and prognosis: etiological and prognostic models

机译:检验因果关系和预后:病因和预后模型

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摘要

Etiological research aims to investigate the causal relationship between putative risk factors (or determinants) and a given disease or other outcome. In contrast, prognostic research aims to predict the probability of a given clinical outcome and in this perspective the pathophysiology of the disease is not an issue. Multivariate modeling is a fundamental tool both to infer causality and to investigate prognostic factors in epidemiological research. The analytical approaches to etiological and prognostic studies are strictly dependent on the research question and imply knowledge of the main statistical procedures for model building and data interpretation. In this paper we describe the application of multivariate statistical modeling in etiological and prognostic research. We will mainly focus on the differences in model building and data interpretation between these two areas of epidemiologic research.
机译:病因学研究旨在调查推定的危险因素(或决定因素)与特定疾病或其他结局之间的因果关系。相反,预后研究旨在预测给定临床结果的可能性,从这个角度来看,该疾病的病理生理学不是问题。多元建模是推断流行病学因果关系和调查预后因素的基本工具。病因和预后研究的分析方法严格取决于研究问题,并且暗含了对模型构建和数据解释的主要统计程序的了解。在本文中,我们描述了多元统计模型在病因和预后研究中的应用。我们将主要关注这两个流行病学研究领域在模型构建和数据解释方面的差异。

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