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Dose-response meta-analysis: application and practice using the R software
Sung Ryul Shim, Jonghoo Lee
Epidemiol Health. 2019;41:e2019006.   Published online March 28, 2019
DOI: https://doi.org/10.4178/epih.e2019006
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  • 19 Citations
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
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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Korean summary
통계프로그램으로서의 R이 대세인 연구환경에서 R을 활용한 체계적인 메타분석 안내서가 요구되어지며 본 연구는 이에 대한 좋은 해답이 될 것이다. 더욱이 본 연구는 용량-반응 메타분석 (Dose-response meta-analysis)의 이론과 더불어 R을 활용한 실습위주의 내용으로 구성되어져 있어 누구나 쉽게 실행할 수 있을 것이다. 본 연구를 통하여 많은 연구자들이 보다 쉽게 본인의 연구분야에 적용하여 관련 연구가 활성화되기를 바란다.
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