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An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability
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 implicat...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10438372/ https://www.ncbi.nlm.nih.gov/pubmed/37556500 http://dx.doi.org/10.1073/pnas.2302491120 |
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author | Zhang, Sam Heck, Patrick R. Meyer, Michelle N. Chabris, Christopher F. Goldstein, Daniel G. Hofman, Jake M. |
author_facet | Zhang, Sam Heck, Patrick R. Meyer, Michelle N. Chabris, Christopher F. Goldstein, Daniel G. Hofman, Jake M. |
author_sort | Zhang, Sam |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10438372 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-104383722023-08-19 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. Proc Natl Acad Sci U S A Social Sciences 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. National Academy of Sciences 2023-08-09 2023-08-15 /pmc/articles/PMC10438372/ /pubmed/37556500 http://dx.doi.org/10.1073/pnas.2302491120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Social Sciences Zhang, Sam Heck, Patrick R. Meyer, Michelle N. Chabris, Christopher F. Goldstein, Daniel G. Hofman, Jake M. An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability |
title | An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability |
title_full | An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability |
title_fullStr | An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability |
title_full_unstemmed | An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability |
title_short | An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability |
title_sort | illusion of predictability in scientific results: even experts confuse inferential uncertainty and outcome variability |
topic | Social Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10438372/ https://www.ncbi.nlm.nih.gov/pubmed/37556500 http://dx.doi.org/10.1073/pnas.2302491120 |
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