Reconsidération de la signification statistique : le rôle des méthodes bayésiennes dans les sciences de la vie
DOI :
https://doi.org/10.18192/osurj.v5i1.7653Résumé
Le raisonnement statistique sous-tend l’interprétation des résultats expérimentaux dans les sciences de la vie. Pendant des décennies, le test d’hypothèses fréquentistes a dominé la pratique de la recherche, la valeur p servant de référence significative. Pourtant, les valeurs p sont souvent mal comprises et limitées dans ce qu’elles révèlent, et les questions de puissance statistique compliquent encore davantage l’inférence. Les méthodes bayésiennes offrent un cadre alternatif qui répond à plusieurs de ces limitations. En incorporant des connaissances préalables et en comparant les probabilités d’hypothèses concurrentes, l’inférence bayésienne permet de produire des mesures plus riches telles que les facteurs bayesiens, les probabilités postérieures et les intervalles crédibles. Cependant, les approches bayésiennes présentent également des défis, notamment la subjectivité des priors et l’intensité computationnelle des modèles complexes. Cette revue synthétise les différences conceptuelles et pratiques entre les approches fréquentistes et bayésiennes, en portant une attention particulière à leurs implications pour la conception expérimentale, les considérations éthiques et l’interprétation dans la recherche biologique moderne. Il examine également comment les normes disciplinaires, la complexité des données et les contraintes normatives influencent les préférences méthodologiques selon les domaines. Plutôt que de présenter les deux paradigmes comme des cadres concurrents, ce travail plaide en faveur du bilinguisme statistique comme fondation nécessaire pour une inférence scientifique transparente, consciente du contexte et reproductible.
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