Facilitating meta‐analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category
Abstract Epidemiological studies relating a particular exposure to a specified disease may present their results in a variety of ways. Often, results are presented as estimated odds ratios (or relative risks) and confidence intervals (CIs) for a number of categories of exposure, for example, by dura...
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crwiley:10.1002/sim.3013 2024-09-30T14:35:57+00:00 Facilitating meta‐analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category Hamling, Jan Lee, Peter Weitkunat, Rolf Ambühl, Mathias 2007 http://dx.doi.org/10.1002/sim.3013 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fsim.3013 https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.3013 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Statistics in Medicine volume 27, issue 7, page 954-970 ISSN 0277-6715 1097-0258 journal-article 2007 crwiley https://doi.org/10.1002/sim.3013 2024-09-03T04:23:19Z Abstract Epidemiological studies relating a particular exposure to a specified disease may present their results in a variety of ways. Often, results are presented as estimated odds ratios (or relative risks) and confidence intervals (CIs) for a number of categories of exposure, for example, by duration or level of exposure, compared with a single reference category, often the unexposed. For systematic literature review, and particularly meta‐analysis, estimates for an alternative comparison of the categories, such as any exposure versus none, may be required. Obtaining these alternative comparisons is not straightforward, as the initial set of estimates is correlated. This paper describes a method for estimating these alternative comparisons based on the ideas originally put forward by Greenland and Longnecker, and provides implementations of the method, developed using Microsoft Excel and SAS. Examples of the method based on studies of smoking and cancer are given. The method also deals with results given by categories of disease (such as histological types of a cancer). The method allows the use of a more consistent comparison when summarizing published evidence, thus potentially improving the reliability of a meta‐analysis. Copyright © 2007 John Wiley & Sons, Ltd. Article in Journal/Newspaper Greenland Wiley Online Library Greenland Statistics in Medicine 27 7 954 970 |
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Abstract Epidemiological studies relating a particular exposure to a specified disease may present their results in a variety of ways. Often, results are presented as estimated odds ratios (or relative risks) and confidence intervals (CIs) for a number of categories of exposure, for example, by duration or level of exposure, compared with a single reference category, often the unexposed. For systematic literature review, and particularly meta‐analysis, estimates for an alternative comparison of the categories, such as any exposure versus none, may be required. Obtaining these alternative comparisons is not straightforward, as the initial set of estimates is correlated. This paper describes a method for estimating these alternative comparisons based on the ideas originally put forward by Greenland and Longnecker, and provides implementations of the method, developed using Microsoft Excel and SAS. Examples of the method based on studies of smoking and cancer are given. The method also deals with results given by categories of disease (such as histological types of a cancer). The method allows the use of a more consistent comparison when summarizing published evidence, thus potentially improving the reliability of a meta‐analysis. Copyright © 2007 John Wiley & Sons, Ltd. |
format |
Article in Journal/Newspaper |
author |
Hamling, Jan Lee, Peter Weitkunat, Rolf Ambühl, Mathias |
spellingShingle |
Hamling, Jan Lee, Peter Weitkunat, Rolf Ambühl, Mathias Facilitating meta‐analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category |
author_facet |
Hamling, Jan Lee, Peter Weitkunat, Rolf Ambühl, Mathias |
author_sort |
Hamling, Jan |
title |
Facilitating meta‐analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category |
title_short |
Facilitating meta‐analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category |
title_full |
Facilitating meta‐analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category |
title_fullStr |
Facilitating meta‐analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category |
title_full_unstemmed |
Facilitating meta‐analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category |
title_sort |
facilitating meta‐analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category |
publisher |
Wiley |
publishDate |
2007 |
url |
http://dx.doi.org/10.1002/sim.3013 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fsim.3013 https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.3013 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland |
genre_facet |
Greenland |
op_source |
Statistics in Medicine volume 27, issue 7, page 954-970 ISSN 0277-6715 1097-0258 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/sim.3013 |
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Statistics in Medicine |
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27 |
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7 |
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954 |
op_container_end_page |
970 |
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1811639150964637696 |