MetaStat: an R shiny app for transforming data into scientific evidence through meta-analysis

Abstract

A systematic review (SR) synthesizes evidence from a research question using comprehensive methods to search, identify, select, evaluate, and extract data from published primary studies. Meta-analysis is a statistical method that combines quantitative results from primary studies addressing the same research question to generate a pooled estimate with a confidence interval. Metaanalyses enhance statistical power, improve precision, and answer questions that individual studies cannot due to limited sample sizes. Combined with SR, they provide valuable insights for evidence-based decision-making. Performing a meta-analysis requires knowledge of statistical software, but this software often lack user-friendly interfaces. To address this, we developed MetaStat, an R Shiny application that simplifies meta-analysis use. MetaStat allows users to select data types (continuous or discrete), upload datasets, and choose appropriate metaanalysis models. It supports fixed/random effects models and subgroup analyses. Results include estimation tables, heterogeneity statistics, and diagnostic measures. The app also generates downloadable forest plots, funnel plots, and Baujat plots. Moreover, MetaStat enables meta-regression by selecting a covariate from the dataset. It is available as a standalone Windows application, via GitHub, or online at ShinyApps.io. This tool enhances accessibility to metaanalysis, bridging the gap between statistical rigor and usability.