Four principles for improved statistical ecology

Gordana Popovic*, Tanya Jane Mason, Szymon Marian Drobniak, Tiago André Marques, Joanne Potts, Rocío Joo, Res Altwegg, Carolyn Claire Isabelle Burns, Michael Andrew McCarthy, Alison Johnston, Shinichi Nakagawa, Louise McMillan, Kadambari Devarajan, Patrick Leo Taggart, Alison Wunderlich, Magdalena M. Mair, Juan Andrés Martínez-Lanfranco, Malgorzata Lagisz, Patrice Pottier

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

1 Citation (Scopus)
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Abstract

1. Increasing attention has been drawn to the misuse of statistical methods over recent 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 disciplines, 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 accounts for the distribution and dependence of your data; (3) emphasise effect sizes to replace statistical significance with ecological relevance; and (4) report your methods 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.
Original languageEnglish
Number of pages16
JournalMethods in Ecology and Evolution
VolumeEarly View
Early online date15 Jan 2024
DOIs
Publication statusE-pub ahead of print - 15 Jan 2024

Keywords

  • HARKing
  • Model assumptions
  • p-hacking
  • Pre-registration
  • p-values
  • Questionable research practices
  • Reproducibility crisis
  • Research waste

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