Most studies account for this within their results. When multiple studies are addressing the same problem or question, it’s to be expected that there will be some potential for error. Conducting Meta-Analyses in R with the metafor Package. This form of research relies on combining statistical results from two or more existing studies. I used this platform to learn the basics of R before using Metafor. If you are new to R, I suggest taking the Introduction to R course on DataCamp (affiliate link). If so – have a look at JASP or Jamovi below. However, since the package requires the use of the R environment, it may be difficult for those who have never used R before to become accustomed to the package so quickly. Their website contains some very useful analysis and plot examples with the corresponding code. Undertaking a meta-analysis of the included studies may not always be feasible due to heterogeneity among these studies. Metafor is one of the many R packages available to conduct meta-analyses and contains the most comprehensive analysis tools. Overall, meta-analysis of the quantitative data could be performed using several software such as: RevMan, Comprehensive Meta-analysis Software, JBI tool, etc. Example forest plot created using Metafor in R.
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