Intervention meta-analysis: application and practice using R software
- Author:
Sung Ryul SHIM
1
;
Seong Jang KIM
Author Information
- Publication Type:Meta-Analysis
- Keywords: Meta-analysis; Meta-regression; Forest plot; Heterogeneity; Publication bias; R software
- MeSH: Forests; Hope; Odds Ratio; Population Characteristics; Publication Bias
- From:Epidemiology and Health 2019;41(1):e2019008-
- CountryRepublic of Korea
- Language:English
- Abstract: The 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.
