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In Search of a Better Reporting of Scientific Results: A Data Probability Language
dc.contributor.author | Martínez-Abraín, Alejandro | |
dc.date.accessioned | 2023-02-16T20:00:17Z | |
dc.date.available | 2023-02-16T20:00:17Z | |
dc.date.issued | 2022-09-28 | |
dc.identifier.citation | Alejandro Martínez-Abraín, In search of a better reporting of scientific results: A data probability language, Acta Oecologica, Volume 117, 2022, 103868, ISSN 1146-609X, https://doi.org/10.1016/j.actao.2022.103868. (https://www.sciencedirect.com/science/article/pii/S1146609X22000583) | es_ES |
dc.identifier.issn | 1146-609X | |
dc.identifier.uri | http://hdl.handle.net/2183/32519 | |
dc.description.abstract | [Abstract] A recent paper published in Trends in Ecology and Evolution suggested a new alternative for the reporting of statistical results, using a language based on evidence against the null hypothesis. I agree that the reporting of null hypothesis statistical testing clearly needs improvement, but the proposal of an evidence-based language has several drawbacks: a) it goes back to the original Fisherian continuous interpretation of p-values, b) at the same time uses some loose categorizations and, c) most importantly, it may provide a wrong idea of what p-values actually are. By saying that there is very strong, strong, moderate, weak or little evidence of an effect, the reader gets the idea that p-values are providing Bayesian-type information on the probability of the null hypothesis given our data. However, p-values are only providing information on the probability of having obtained our data (or more extreme data), under the trueness of the null hypothesis. That is why I suggest reporting results using a data probability-based language, together with a previous and separate specification of the magnitude of the effects. | es_ES |
dc.description.sponsorship | AMA was supported by Xunta de Galicia, project ED431C 2018/57 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2018/57 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.uri | https://doi.org/10.1016/j.actao.2022.103868 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 4.0 Internacional | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | p-values | es_ES |
dc.subject | Evidence-based language | es_ES |
dc.subject | Data probability language | es_ES |
dc.subject | Good praxis | es_ES |
dc.subject | Reporting of results | es_ES |
dc.subject | NHST | es_ES |
dc.title | In Search of a Better Reporting of Scientific Results: A Data Probability Language | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Acta Oecologica | es_ES |
UDC.volume | 117 | es_ES |
UDC.issue | November 2022 | es_ES |
UDC.startPage | 103868 | es_ES |
dc.identifier.doi | 10.1016/j.actao.2022.103868 |
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