Meta-analysis parameters computation: a Python approach to facilitate the crossing of experimental conditions

Flavien Quijoux, Charles Truong, Aliénor Vienne-Jumeau, Laurent Oudre, François Bertin-Hugault, Philippe Zawieja, Marie Lefèvre, Pierre-Paul Vidal, Damien Ricard

Abstract: Meta-analysis is a data aggregation method that establishes an overall and objective level of evidence based on the results of several studies. It is necessary to maintain a high level of homogeneity in the aggregation of data collected from a systematic literature review. However, the current tools do not allow a cross-referencing of the experimental conditions that could explain the heterogeneity observed between studies. This article aims at proposing a Python programming code containing several functions allowing the analysis and rapid visualization of data from many studies, while allowing the possibility of cross-checking the results by experimental condition.