at Google ScholarTitle data
Popovic, Gordana ; Mason, Tanya Jane ; Drobniak, Szymon Marian ; Marques, Tiago André ; Potts, Joanne ; Joo, Rocío ; Altwegg, Res ; Burns, Carolyn Claire Isabelle ; McCarthy, Michael Andrew ; Johnston, Alison ; Nakagawa, Shinichi ; McMillan, Louise ; Devarajan, Kadambari ; Taggart, Patrick Leo ; Wunderlich, Alison ; Mair, Magdalena ; Martínez-Lanfranco, Juan Andrés ; Lagisz, Malgorzata ; Pottier, Patrice:
Four principles for improved statistical ecology.
In: Methods in Ecology and Evolution.
Vol. 15
(2024)
Issue 2
.
- pp. 266-281.
ISSN 2041-210X
DOI: https://doi.org/10.1111/2041-210X.14270
This is the latest version of this item.
Abstract in another language
1. Increasing attention has been drawn to the misuse of statistical methods over re-cent years, with particular concern about the prevalence of practices such as poor experimental design, cherry picking and inadequate reporting. These failures are largely unintentional and no more common in ecology than in other scientific dis-ciplines, with many of them easily remedied given the right guidance.
2. Originating from a discussion at the 2020 International Statistical Ecology Conference, we show how ecologists can build their research following four guiding principles for impactful statistical research practices: (1) define a focussed research question, then plan sampling and analysis to answer it; (2) develop a model that ac-counts for the distribution and dependence of your data; (3) emphasise effect sizes to replace statistical significance with ecological relevance; and (4) report your meth-ods and findings in sufficient detail so that your research is valid and reproducible.
3. These principles provide a framework for experimental design and reporting that guards against unsound practices. Starting with a well-defined research question allows researchers to create an efficient study to answer it, and guards against poor research practices that lead to poor estimation of the direction, magnitude, and uncertainty of ecological relationships, and to poor replicability. Correct and appropriate statistical models give sound conclusions. Good reporting practices and a focus on ecological relevance make results impactful and replicable.
4. Illustrated with two examples—an experiment to study the impact of disturbance on upland wetlands, and an observational study on blue tit colouring—this paper explains the rationale for the selection and use of effective statistical practices and provides practical guidance for ecologists seeking to improve their use of statistical methods.
Further data
| Item Type: | Article in a journal |
|---|---|
| Refereed: | Yes |
| Keywords: | HARKing; model assumptions; p-hacking; pre-registration; p-values; questionable research practices; reproducibility crisis; research waste |
| Institutions of the University: | Faculties > Faculty of Biology, Chemistry and Earth Sciences Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Biology Research Institutions > Central research institutes > Bayreuth Center of Ecology and Environmental Research- BayCEER Faculties Research Institutions Research Institutions > Central research institutes |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 500 Science 500 Science > 500 Natural sciences 500 Science > 570 Life sciences, biology |
| Date Deposited: | 24 Jan 2024 06:20 |
| Last Modified: | 12 Sep 2024 12:27 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/88324 |
Available Versions of this Item
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Four principles for improved statistical ecology. (deposited 07 Feb 2023 07:51)
- Four principles for improved statistical ecology. (deposited 24 Jan 2024 06:20) [Currently Displayed]