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Quantity and Quality in Scientific Productivity: The Tilted Funnel Goes Bayesian
The equal odds baseline model of creative scientific productivity proposes that the number of high-quality works depends linearly on the number of total works. In addition, the equal odds baseline implies that the percentage of high-quality works and total number of works are uncorrelated. The tilte...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680221/ https://www.ncbi.nlm.nih.gov/pubmed/36412775 http://dx.doi.org/10.3390/jintelligence10040095 |
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author | Forthmann, Boris Dumas, Denis |
author_facet | Forthmann, Boris Dumas, Denis |
author_sort | Forthmann, Boris |
collection | PubMed |
description | The equal odds baseline model of creative scientific productivity proposes that the number of high-quality works depends linearly on the number of total works. In addition, the equal odds baseline implies that the percentage of high-quality works and total number of works are uncorrelated. The tilted funnel hypothesis proposes that the linear regression implied by the equal odds baseline is heteroscedastic with residual variance in the quality of work increasing as a function of quantity. The aim of the current research is to leverage Bayesian statistical modeling of the equal odds baseline. Previous work has examined the tilted funnel by means of frequentist quantile regression, but Bayesian quantile regression based on the asymmetric Laplace model allows for only one conditional quantile at a time. Hence, we propose additional Bayesian methods, including Poisson modeling to study conditional variance as a function of quantity. We use a classical small sample of eminent neurosurgeons, as well as the brms Bayesian R package, to accomplish this work. In addition, we provide open code and data to allow interested researchers to extend our work and utilize the proposed modeling alternatives. |
format | Online Article Text |
id | pubmed-9680221 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96802212022-11-23 Quantity and Quality in Scientific Productivity: The Tilted Funnel Goes Bayesian Forthmann, Boris Dumas, Denis J Intell Article The equal odds baseline model of creative scientific productivity proposes that the number of high-quality works depends linearly on the number of total works. In addition, the equal odds baseline implies that the percentage of high-quality works and total number of works are uncorrelated. The tilted funnel hypothesis proposes that the linear regression implied by the equal odds baseline is heteroscedastic with residual variance in the quality of work increasing as a function of quantity. The aim of the current research is to leverage Bayesian statistical modeling of the equal odds baseline. Previous work has examined the tilted funnel by means of frequentist quantile regression, but Bayesian quantile regression based on the asymmetric Laplace model allows for only one conditional quantile at a time. Hence, we propose additional Bayesian methods, including Poisson modeling to study conditional variance as a function of quantity. We use a classical small sample of eminent neurosurgeons, as well as the brms Bayesian R package, to accomplish this work. In addition, we provide open code and data to allow interested researchers to extend our work and utilize the proposed modeling alternatives. MDPI 2022-11-01 /pmc/articles/PMC9680221/ /pubmed/36412775 http://dx.doi.org/10.3390/jintelligence10040095 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Forthmann, Boris Dumas, Denis Quantity and Quality in Scientific Productivity: The Tilted Funnel Goes Bayesian |
title | Quantity and Quality in Scientific Productivity: The Tilted Funnel Goes Bayesian |
title_full | Quantity and Quality in Scientific Productivity: The Tilted Funnel Goes Bayesian |
title_fullStr | Quantity and Quality in Scientific Productivity: The Tilted Funnel Goes Bayesian |
title_full_unstemmed | Quantity and Quality in Scientific Productivity: The Tilted Funnel Goes Bayesian |
title_short | Quantity and Quality in Scientific Productivity: The Tilted Funnel Goes Bayesian |
title_sort | quantity and quality in scientific productivity: the tilted funnel goes bayesian |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680221/ https://www.ncbi.nlm.nih.gov/pubmed/36412775 http://dx.doi.org/10.3390/jintelligence10040095 |
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