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Dose-response meta-analysis: application and practice using the R software
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Sung Ryul Shim, Jonghoo Lee
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Epidemiol Health. 2019;41:e2019006. Published online March 28, 2019
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DOI: https://doi.org/10.4178/epih.e2019006
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20,332
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575
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50
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 Abstract
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 PDF Supplementary Material
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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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Summary
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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Diagnostic test accuracy: application and practice using R software
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Sung Ryul Shim, Seong-Jang Kim, Jonghoo Lee
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Epidemiol Health. 2019;41:e2019007. Published online March 28, 2019
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DOI: https://doi.org/10.4178/epih.e2019007
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24,128
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712
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108
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67
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Abstract
Summary
PDFSupplementary Material
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Abstract
The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were “metaprop” and “metabin” for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of “mada” for a summarized receiver-operating characteristic (ROC) curve; and “metareg” for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.
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Summary
Korean summary
통계프로그램으로서의 R이 대세인 연구환경에서 R을 활용한 체계적인 메타분석 안내서가 요구되어지며 본 연구는 이에 대한 좋은 해답이 될 것이다. 더욱이 본 연구는 진단검사 메타분석 (Diagnostic test accuracy)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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Citations
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Network meta-analysis: application and practice using R software
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Sung Ryul Shim, Seong-Jang Kim, Jonghoo Lee, Gerta Rücker
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Epidemiol Health. 2019;41:e2019013. Published online April 8, 2019
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DOI: https://doi.org/10.4178/epih.e2019013
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Abstract
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Abstract
The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software. We conducted a network meta-analysis using two approaches: Bayesian and frequentist methods. The corresponding R packages were “gemtc” for the Bayesian approach and “netmeta” for the frequentist approach. In estimating a network meta-analysis model using a Bayesian framework, the “rjags” package is a common tool. “rjags” implements Markov chain Monte Carlo simulation with a graphical output. The estimated overall effect sizes, test for heterogeneity, moderator effects, and publication bias were reported using R software. The authors focus on two flexible models, Bayesian and frequentist, to determine overall effect sizes in network meta-analysis. This study focused on the practical methods of network meta-analysis rather than theoretical concepts, making the material easy to understand for Korean researchers who did not major in statistics. The authors hope that this study will help many Korean researchers to perform network meta-analyses and conduct related research more easily with R software.
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Summary
Korean summary
통계프로그램으로서의 R이 대세인 연구환경에서 R을 활용한 체계적인 메타분석 안내서가 요구되어지며 본 연구는 이에 대한 좋은 해답이 될 것이다. 더욱이 본 연구는 네트워크 메타분석 (Network 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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