Severity and Trustworthy Evidence: Foundational Problems versus Misuses of Frequentist Testing.

For model-based frequentist statistics, based on a parametric statistical model , the trustworthiness of the ensuing evidence depends crucially on (i) the validity of the probabilistic assumptions comprising , (ii) the optimality of the inference procedures employed, and (iii) the adequateness of th...

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Publicado en:Philosophy of Science Vol. 89; no. 2; pp. 378 - 398
Autor principal: Spanos, Aris
Formato: Artículo
Publicado: Cambridge University Press Apr2022
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Severity and Trustworthy Evidence: Foundational Problems versus Misuses of Frequentist Testing.
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        au: Spanos, Aris
        affil: Virginia Tech, Blacksburg, VA, USA
      su:
        Trust
        Frequentist statistics
        Statistical models
        Parametric modeling
        Sample size (Statistics)
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        subj:
          Trust
          Frequentist statistics
          Statistical models
          Parametric modeling
          Sample size (Statistics)
      ab: For model-based frequentist statistics, based on a parametric statistical model , the trustworthiness of the ensuing evidence depends crucially on (i) the validity of the probabilistic assumptions comprising , (ii) the optimality of the inference procedures employed, and (iii) the adequateness of the sample size (n) 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 n 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.
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