Ten Top Tips for Reviewing Statistics: A Guide for Ecologists

post provided by Dr Mark Brewer.

Mark is a statistician with Biomathematics & Statistics Scotland, based in Aberdeen. His main statistical research interests are Species Distribution Modelling, Compositional Data Analysis, Bayesian Mixture Modelling and Bayesian Ordinal Regression. Mark was one of the presenters at the UK half of the Methods in Ecology and Evolution 5th Anniversary Symposium in April. You can watch his talk, ‘Model Selection and the Cult of AIC’ here.

The level of statistical analysis in ecology journals is far higher than in most other disciplines. Ecological journals lead the way in the development of statistical methodology, necessitated by challenging practical problems involving complex data sets. As a statistician, publishing also in hydrology, soil science, social science and forensic science journals, I’ve found papers in those areas are much more likely to only use well-established methods than papers in ecology.

Here’s the big question though: why then do I have the most difficulty with ecological journals when it comes to statistical analyses? Let’s be clear here: when I say “difficulty”, I mean I receive reviews which are just plain wrong. Most statisticians I’ve spoken to who work in ecology have anecdotes from reviews which demonstrate a lack of understanding by the non-statistician reviewer (including the all-too-frequent “perhaps you should consult a statistician”). So, why the apparent disconnect?

The difference seems to be in how non-statisticians in different disciplines treat the statistics in a paper. In many subject areas, reviewers are almost deferential to the statistical analysis; in ecology, reviewers can be forthright in their condemnation, often without justification. Reviewers have every right to question the statistical analysis in a paper, but the authors have the exact same right to expect a high quality review from a genuine expert in the field. Has ecology become blasé about statistics? Continue reading