Causal inference based on counterfactuals
<p>Abstract</p> <p>Background</p> <p>The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies.</p> <p>Discussion</p> <p>This paper provides an overview on the count...
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doaj-7b6bb83e5e134d8c8a7b27c098144fd92020-11-25T00:29:51ZengBMCBMC Medical Research Methodology1471-22882005-09-01512810.1186/1471-2288-5-28Causal inference based on counterfactualsHöfler M<p>Abstract</p> <p>Background</p> <p>The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies.</p> <p>Discussion</p> <p>This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures.</p> <p>Summary</p> <p>Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept.</p> http://www.biomedcentral.com/1471-2288/5/28 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Höfler M |
spellingShingle |
Höfler M Causal inference based on counterfactuals BMC Medical Research Methodology |
author_facet |
Höfler M |
author_sort |
Höfler M |
title |
Causal inference based on counterfactuals |
title_short |
Causal inference based on counterfactuals |
title_full |
Causal inference based on counterfactuals |
title_fullStr |
Causal inference based on counterfactuals |
title_full_unstemmed |
Causal inference based on counterfactuals |
title_sort |
causal inference based on counterfactuals |
publisher |
BMC |
series |
BMC Medical Research Methodology |
issn |
1471-2288 |
publishDate |
2005-09-01 |
description |
<p>Abstract</p> <p>Background</p> <p>The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies.</p> <p>Discussion</p> <p>This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures.</p> <p>Summary</p> <p>Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept.</p> |
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http://www.biomedcentral.com/1471-2288/5/28 |
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AT hoflerm causalinferencebasedoncounterfactuals |
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