System Architecture and Statistical Methodology
The meta-analysis feature is implemented as a cohesive module that follows a clear, multi-layered architecture, ensuring separation of concerns between data retrieval, statistical computation, and presentation.
Summary
This report provides a comprehensive technical overview of the meta-analysis functionality implemented within the RevPro systematic review management platform. The module is designed to perform robust, publication-quality statistical synthesis for quantitative data extracted from primary studies. We detail the backend architecture, the specific statistical formulas and methodologies employed, the approaches used for data visualization, and the measures taken to ensure the reliability and validity of the calculations. The system supports meta-analyses for dichotomous outcomes (effectiveness), single proportions (prevalence), and continuous outcomes (mean differences), incorporating fixed-effect and random-effects models, heterogeneity assessment, formal subgroup analysis with a test for interaction, and publication bias testing using weighted least squares regression. A key feature is the implementation of a conditional continuity correction to preserve data integrity while handling sparse data. Furthermore, an advanced Network Meta-Analysis (NMA) capability has been integrated, leveraging external R scripting for complex indirect comparisons.
Read technical overview of the meta-analysis functionality implemented within the RevPro here.