Multiple perspectives on inference for two simple statistical scenarios

van Dongen, Noah N. N., van Doorn, Johnny B., Gronan, Quentin F, van Ravenzwaaij, Don, Hoekstra, Rink, Haucke, Matthias N., Lakens, Daniel, Hennig, Christian, Morey, Ricahrd D. ORCID: https://orcid.org/0000-0001-9220-3179, Homer, Saskia ORCID: https://orcid.org/0000-0003-1399-4895, Gelman, Andrew, Sprenger, Jan and Wagenmakers, Eric-Jan 2019. Multiple perspectives on inference for two simple statistical scenarios. American Statistician 73 (s1) , pp. 328-339. 10.1080/00031305.2019.1565553

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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.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Psychology
Publisher:	Taylor & Francis
ISSN:	0003-1305
Date of First Compliant Deposit:	29 January 2019
Date of Acceptance:	4 December 2018
Last Modified:	04 May 2023 04:26
URI:	https://orca.cardiff.ac.uk/id/eprint/118950

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