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Meta-analysis is a data aggregation method that establishes an overall andobjective level of evidence based on the results of several studies. It isnecessary to maintain a high level of homogeneity in the aggregation of datacollected from a systematic literature review. However, the current tools donot allow a cross-referencing of the experimental conditions that could explainthe heterogeneity observed between studies. This article aims at proposing aPython programming code containing several functions allowing the analysis andrapid visualization of data from many studies, while allowing the possibilityof cross-checking the results by experimental condition.

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