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Reply to Rouder (2014): good frequentist properties raise confidence.
Sanborn, Adam N; Hills, Thomas T; Dougherty, Michael R; Thomas, Rick P; Yu, Erica C; Sprenger, Amber M.
Afiliación
  • Sanborn AN; Department of Psychology, University of Warwick, Coventry, CV4 7AL, UK, A.N.Sanborn@warwick.ac.uk.
Psychon Bull Rev ; 21(2): 309-11, 2014 Apr.
Article en En | MEDLINE | ID: mdl-24614967
ABSTRACT
Established psychological results have been called into question by demonstrations that statistical significance is easy to achieve, even in the absence of an effect. One often-warned-against practice, choosing when to stop the experiment on the basis of the results, is guaranteed to produce significant results. In response to these demonstrations, Bayes factors have been proposed as an antidote to this practice, because they are invariant with respect to how an experiment was stopped. Should researchers only care about the resulting Bayes factor, without concern for how it was produced? Yu, Sprenger, Thomas, and Dougherty (2014) and Sanborn and Hills (2014) demonstrated that Bayes factors are sometimes strongly influenced by the stopping rules used. However, Rouder (2014) has provided a compelling demonstration that despite this influence, the evidence supplied by Bayes factors remains correct. Here we address why the ability to influence Bayes factors should still matter to researchers, despite the correctness of the evidence. We argue that good frequentist properties mean that results will more often agree with researchers' statistical intuitions, and good frequentist properties control the number of studies that will later be refuted. Both help raise confidence in psychological results.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proyectos de Investigación / Interpretación Estadística de Datos / Modelos Estadísticos / Teorema de Bayes Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Psychon Bull Rev Asunto de la revista: PSICOLOGIA Año: 2014 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proyectos de Investigación / Interpretación Estadística de Datos / Modelos Estadísticos / Teorema de Bayes Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Psychon Bull Rev Asunto de la revista: PSICOLOGIA Año: 2014 Tipo del documento: Article