Spanos, Aris2024-02-122024-02-122022-02-100031-8248https://hdl.handle.net/10919/117931For model-based frequentist statistics, based on a parametric statistical model ${{\cal M}_\theta }({\bf{x}})$, the trustworthiness of the ensuing evidence depends crucially on (i) the validity of the probabilistic assumptions comprising ${{\cal M}_\theta }({\bf{x}})$, (ii) the optimality of the inference procedures employed, and (iii) the adequateness of the sample size (<i>n</i>) to learn from data by securing (i)–(ii). It is argued that the criticism of the postdata severity evaluation of testing results based on a small <i>n</i> by Rochefort-Maranda (2020) is meritless because it conflates [a] misuses of testing with [b] genuine foundational problems. Interrogating this criticism reveals several misconceptions about trustworthy evidence and estimation-based effect sizes, which are uncritically embraced by the replication crisis literature.Pages 378-39720 page(s)application/pdfenIn CopyrightArticle - Refereedhttps://doi.org/10.1017/psa.2021.238921539-767X