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An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability.
Zhang, Sam; Heck, Patrick R; Meyer, Michelle N; Chabris, Christopher F; Goldstein, Daniel G; Hofman, Jake M.
Afiliação
  • Zhang S; Department of Applied Mathematics, University of Colorado, Boulder, CO 80309.
  • Heck PR; Office of Research, Consumer Financial Protection Bureau, Washington, DC 20552.
  • Meyer MN; Department of Bioethics & Decision Sciences, Geisinger Health System, Danville, PA 17822.
  • Chabris CF; Department of Bioethics & Decision Sciences, Geisinger Health System, Danville, PA 17822.
  • Goldstein DG; Microsoft Research, New York, NY 10012.
  • Hofman JM; Microsoft Research, New York, NY 10012.
Proc Natl Acad Sci U S A ; 120(33): e2302491120, 2023 Aug 15.
Article em En | MEDLINE | ID: mdl-37556500
Traditionally, scientists have placed more emphasis on communicating inferential uncertainty (i.e., the precision of statistical estimates) compared to outcome variability (i.e., the predictability of individual outcomes). Here, we show that this can lead to sizable misperceptions about the implications of scientific results. Specifically, we present three preregistered, randomized experiments where participants saw the same scientific findings visualized as showing only inferential uncertainty, only outcome variability, or both and answered questions about the size and importance of findings they were shown. Our results, composed of responses from medical professionals, professional data scientists, and tenure-track faculty, show that the prevalent form of visualizing only inferential uncertainty can lead to significant overestimates of treatment effects, even among highly trained experts. In contrast, we find that depicting both inferential uncertainty and outcome variability leads to more accurate perceptions of results while appearing to leave other subjective impressions of the results unchanged, on average.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2023 Tipo de documento: Article