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논문KCI 등재

Intervention meta-analysis: application and practice using R software

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초록

knowlThe objective of this study was to describe general approaches for intervention meta-analysis available for quantitative data synthesis using the R software. We conducted an intervention meta-analysis using two types of data, continuous and binary, characterized by mean difference and odds ratio, respectively. The package commands for the R software were “metacont”, “metabin”, and “metagen” for the overall effect size, “forest” for forest plot, “metareg” for meta-regression analysis, and “funnel” and “metabias” for the publication bias. The estimated overall effect sizes, test for heterogeneity and moderator effect, and the publication bias were reported using the R software. In particular, the authors indicated methods for calculating the effect sizes of the target studies in intervention meta-analysis. This study focused on the practical methods of intervention meta-analysis, rather than the theoretical concepts, for researchers with no major in statistics. Through this study, the authors hope that many researchers will use the R software to more readily perform the intervention meta-analysis and that this will in turn generate further related research.

Abstract

knowlThe objective of this study was to describe general approaches for intervention meta-analysis available for quantitative data synthesis using the R software. We conducted an intervention meta-analysis using two types of data, continuous and binary, characterized by mean difference and odds ratio, respectively. The package commands for the R software were “metacont”, “metabin”, and “metagen” for the overall effect size, “forest” for forest plot, “metareg” for meta-regression analysis, and “funnel” and “metabias” for the publication bias. The estimated overall effect sizes, test for heterogeneity and moderator effect, and the publication bias were reported using the R software. In particular, the authors indicated methods for calculating the effect sizes of the target studies in intervention meta-analysis. This study focused on the practical methods of intervention meta-analysis, rather than the theoretical concepts, for researchers with no major in statistics. Through this study, the authors hope that many researchers will use the R software to more readily perform the intervention meta-analysis and that this will in turn generate further related research.

참고문헌 (6)

  1. Hwang SD, "Meta-analysis: from forest plot to network meta-analysis", pp.12~178 (2018), Hannarae
  2. Shim SR, "Intervention meta-analysis using R software" (2019), SDB Lab
  3. 심성률, "중재 메타분석을 위한 STATA 명령어", 보건정보통계학회지, 41(1), pp.123~134 (2016), 한국보건정보통계학회[DOI]
  4. "Cochrane handbook for systematic reviews of interventions. Version 5.1.0" (2011)[URL]
  5. Borensein M, "Introduction to meta-analysis", pp.20~28 (2019), John Wiley & Sons
  6. "R packages"[URL]

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