Ince, R. A.A. , Paton, A. T., Kay, J. W. and Schyns, P. G. (2021) Bayesian inference of population prevalence. eLife, 10, e62461. (doi: 10.7554/eLife.62461) (PMID:34612811) (PMCID:PMC8494477)
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Abstract
Within neuroscience, psychology, and neuroimaging, the most frequently used statistical approach is null hypothesis significance testing (NHST) of the population mean. An alternative approach is to perform NHST within individual participants and then infer, from the proportion of participants showing an effect, the prevalence of that effect in the population. We propose a novel Bayesian method to estimate such population prevalence that offers several advantages over population mean NHST. This method provides a population-level inference that is currently missing from study designs with small participant numbers, such as in traditional psychophysics and in precision imaging. Bayesian prevalence delivers a quantitative population estimate with associated uncertainty instead of reducing an experiment to a binary inference. Bayesian prevalence is widely applicable to a broad range of studies in neuroscience, psychology, and neuroimaging. Its emphasis on detecting effects within individual participants can also help address replicability issues in these fields.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Paton, Mr Angus and Schyns, Professor Philippe and Kay, Dr James and Ince, Dr Robin |
| Creator Roles: | Ince, R. A.A.Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Software, Visualization, Writing – original draft, Writing – review and editing Paton, A. T.Data curation, Formal analysis, Validation, Visualization, Writing – review and editing Kay, J. W.Conceptualization, Formal analysis, Investigation, Methodology, Software, Writing – review and editing Schyns, P. G.Conceptualization, Funding acquisition, Writing – review and editing |
| Authors: | Ince, R. A.A., Paton, A. T., Kay, J. W., and Schyns, P. G. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience College of Science and Engineering > School of Mathematics and Statistics > Statistics |
| Journal Name: | eLife |
| Publisher: | eLife Sciences Publications |
| ISSN: | 2050-084X |
| ISSN (Online): | 2050-084X |
| Copyright Holders: | Copyright © 2021 Ince et al. |
| First Published: | First published in eLife 10: e62461 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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