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Model-averaged Bayesian t tests

M. Maier, F. Bartoš, DS. Quintana, F. Dablander, DV. den Bergh, M. Marsman, A. Ly, EJ. Wagenmakers

. 2025 ; 32 (3) : 1007-1031. [pub] 20241107

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, přehledy

Perzistentní odkaz   https://www.medvik.cz/link/bmc25015591

Grantová podpora
EP-C-17-017 EPA - United States CEP - Centrální evidence projektů
16.Vici.170.083, 451-17-017 Nederlandse Organisatie voor Wetenschappelijk Onderzoek
743086 UNIFY H2020 European Research Council

E-zdroje Online Plný text

NLK ProQuest Central od 2011-02-01 do Před 1 rokem
Medline Complete (EBSCOhost) od 2011-02-01 do Před 1 rokem
Health & Medicine (ProQuest) od 2011-02-01 do Před 1 rokem
Psychology Database (ProQuest) od 2011-02-01 do Před 1 rokem

One of the most common statistical analyses in experimental psychology concerns the comparison of two means using the frequentist t test. However, frequentist t tests do not quantify evidence and require various assumption tests. Recently, popularized Bayesian t tests do quantify evidence, but these were developed for scenarios where the two populations are assumed to have the same variance. As an alternative to both methods, we outline a comprehensive t test framework based on Bayesian model averaging. This new t test framework simultaneously takes into account models that assume equal and unequal variances, and models that use t-likelihoods to improve robustness to outliers. The resulting inference is based on a weighted average across the entire model ensemble, with higher weights assigned to models that predicted the observed data well. This new t test framework provides an integrated approach to assumption checks and inference by applying a series of pertinent models to the data simultaneously rather than sequentially. The integrated Bayesian model-averaged t tests achieve robustness without having to commit to a single model following a series of assumption checks. To facilitate practical applications, we provide user-friendly implementations in JASP and via the RoBTT package in R . A tutorial video is available at https://www.youtube.com/watch?v=EcuzGTIcorQ.

Citace poskytuje Crossref.org

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