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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...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2006
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1431532/ https://www.ncbi.nlm.nih.gov/pubmed/16441879 http://dx.doi.org/10.1186/1742-5573-3-2 |
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author | Newman, Stephen C |
author_facet | Newman, Stephen C |
author_sort | Newman, Stephen C |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-1431532 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-14315322006-04-06 Causal analysis of case-control data Newman, Stephen C Epidemiol Perspect Innov Methodology 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. BioMed Central 2006-01-27 /pmc/articles/PMC1431532/ /pubmed/16441879 http://dx.doi.org/10.1186/1742-5573-3-2 Text en Copyright © 2006 Newman; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Newman, Stephen C Causal analysis of case-control data |
title | Causal analysis of case-control data |
title_full | Causal analysis of case-control data |
title_fullStr | Causal analysis of case-control data |
title_full_unstemmed | Causal analysis of case-control data |
title_short | Causal analysis of case-control data |
title_sort | causal analysis of case-control data |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1431532/ https://www.ncbi.nlm.nih.gov/pubmed/16441879 http://dx.doi.org/10.1186/1742-5573-3-2 |
work_keys_str_mv | AT newmanstephenc causalanalysisofcasecontroldata |