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Multiple Perspectives on Inference for Two Simple Statistical Scenarios

Van Dongen, NNN; Van Doorn, JB; Gronau, QF; Van Ravenzwaaij, D; Hoekstra, R; Haucke, MN; Lakens, D; ... Wagenmakers, E-J; + view all (2019) Multiple Perspectives on Inference for Two Simple Statistical Scenarios. The American Statistician , 73 (S1) pp. 328-339. 10.1080/00031305.2019.1565553. Green open access

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Abstract

When data analysts operate within different statistical frameworks (e.g., frequentist versus Bayesian, emphasis on estimation versus emphasis on testing), how does this impact the qualitative conclusions that are drawn for real data? To study this question empirically we selected from the literature two simple scenarios—involving a comparison of two proportions and a Pearson correlation—and asked four teams of statisticians to provide a concise analysis and a qualitative interpretation of the outcome. The results showed considerable overall agreement; nevertheless, this agreement did not appear to diminish the intensity of the subsequent debate over which statistical framework is more appropriate to address the questions at hand.

Type: Article
Title: Multiple Perspectives on Inference for Two Simple Statistical Scenarios
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/00031305.2019.1565553
Publisher version: https://doi.org/10.1080/00031305.2019.1565553
Language: English
Additional information: Copyright © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Keywords: Frequentist or Bayesian, Multilab analysis, Statistical paradigms, Testing or estimation
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10074227
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