Chapter 6.2

Causality theory for policy uses of epidemiological measures Sander Greenland This paper provides an introduction to measures of causal effects and focuses on underlying conceptual models, definitions and drawbacks of special relevance to policy formulation based on epidemiological data. It begins b...

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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.378.6891 2023-05-15T16:28:25+02:00 Chapter 6.2 The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.378.6891 http://whqlibdoc.who.int/publications/2002/9241545518_Chap6.2.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.378.6891 http://whqlibdoc.who.int/publications/2002/9241545518_Chap6.2.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://whqlibdoc.who.int/publications/2002/9241545518_Chap6.2.pdf text ftciteseerx 2016-09-18T00:14:02Z Causality theory for policy uses of epidemiological measures Sander Greenland This paper provides an introduction to measures of causal effects and focuses on underlying conceptual models, definitions and drawbacks of special relevance to policy formulation based on epidemiological data. It begins by describing a foundation for critical analysis based on counterfactuals and potential outcomes. It then describes analyses based on hypothetical outcome removal and rejects them as potentially misleading. It is argued that one should analyse measures within a multivariate framework to capture the impact of major sources of morbidity and mortality. This framework can clarify what is captured and missed by any proposed summary measure of population health, and shows that the concept of summary measure can and should be extended to multidimensional indices. Text Greenland Unknown Greenland
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description Causality theory for policy uses of epidemiological measures Sander Greenland This paper provides an introduction to measures of causal effects and focuses on underlying conceptual models, definitions and drawbacks of special relevance to policy formulation based on epidemiological data. It begins by describing a foundation for critical analysis based on counterfactuals and potential outcomes. It then describes analyses based on hypothetical outcome removal and rejects them as potentially misleading. It is argued that one should analyse measures within a multivariate framework to capture the impact of major sources of morbidity and mortality. This framework can clarify what is captured and missed by any proposed summary measure of population health, and shows that the concept of summary measure can and should be extended to multidimensional indices.
author2 The Pennsylvania State University CiteSeerX Archives
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