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Dose-response meta-analysis: application and practice using the R software

The objective of this study was to describe the general approaches of dose-response meta-analysis (DRMA) available for the quantitative synthesis of data using the R software. We conducted a DRMA using two types of data, the difference of means in continuous data and the odds ratio in binary data. T...

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Autores principales: Shim, Sung Ryul, Lee, Jonghoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Epidemiology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6635664/
https://www.ncbi.nlm.nih.gov/pubmed/30999740
http://dx.doi.org/10.4178/epih.e2019006
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author Shim, Sung Ryul
Lee, Jonghoo
author_facet Shim, Sung Ryul
Lee, Jonghoo
author_sort Shim, Sung Ryul
collection PubMed
description The objective of this study was to describe the general approaches of dose-response meta-analysis (DRMA) available for the quantitative synthesis of data using the R software. We conducted a DRMA using two types of data, the difference of means in continuous data and the odds ratio in binary data. The package commands of the R software were “doseresmeta” for the overall effect sizes that were separated into a linear model, quadratic model, and restricted cubic split model for better understanding. The effect sizes according to the dose and a test for linearity were demonstrated and interpreted by analyzing one-stage and two-stage DRMA. The authors examined several flexible models of exposure to pool study-specific trends and made a graphical presentation of the dose-response trend. This study focused on practical methods of DRMA rather than theoretical concepts for researchers who did not major in statistics. The authors hope that this study will help many researchers use the R software to perform DRMAs more easily, and that related research will be pursued.
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spelling pubmed-66356642019-07-25 Dose-response meta-analysis: application and practice using the R software Shim, Sung Ryul Lee, Jonghoo Epidemiol Health Methods The objective of this study was to describe the general approaches of dose-response meta-analysis (DRMA) available for the quantitative synthesis of data using the R software. We conducted a DRMA using two types of data, the difference of means in continuous data and the odds ratio in binary data. The package commands of the R software were “doseresmeta” for the overall effect sizes that were separated into a linear model, quadratic model, and restricted cubic split model for better understanding. The effect sizes according to the dose and a test for linearity were demonstrated and interpreted by analyzing one-stage and two-stage DRMA. The authors examined several flexible models of exposure to pool study-specific trends and made a graphical presentation of the dose-response trend. This study focused on practical methods of DRMA rather than theoretical concepts for researchers who did not major in statistics. The authors hope that this study will help many researchers use the R software to perform DRMAs more easily, and that related research will be pursued. Korean Society of Epidemiology 2019-03-28 /pmc/articles/PMC6635664/ /pubmed/30999740 http://dx.doi.org/10.4178/epih.e2019006 Text en ©2019, Korean Society of Epidemiology This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods
Shim, Sung Ryul
Lee, Jonghoo
Dose-response meta-analysis: application and practice using the R software
title Dose-response meta-analysis: application and practice using the R software
title_full Dose-response meta-analysis: application and practice using the R software
title_fullStr Dose-response meta-analysis: application and practice using the R software
title_full_unstemmed Dose-response meta-analysis: application and practice using the R software
title_short Dose-response meta-analysis: application and practice using the R software
title_sort dose-response meta-analysis: application and practice using the r software
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6635664/
https://www.ncbi.nlm.nih.gov/pubmed/30999740
http://dx.doi.org/10.4178/epih.e2019006
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