: All quantitative research methods are based on models. All statistical tests, all summary statistics, all raw data, and even our ideas are models. Failing to appreciate the ubiquity of models leads to misunderstanding the epistemology of science itself. Conversely, realizing that all science is an act in model building leads to more creative and robust inquiries, and, ultimately, better inference.
Ecological “bright spots” and the challenge of residuals-based assessment
The bright spots approach aims to assess the performance of managed ecosystems by comparing certain ecological outcomes, while controlling for other known drivers of the outcome via a statistical model; in effect, ranking sites based on their residuals from the fitted model. While the method has the potential to reduce bias in comparing different sites, the resulting assessment may come with high variance.
Abandon ANOVA-type experiments
Simple “comparison of means” experiments … train our brains to think that this is the goal of science – to discover if an effect exists.
When do we introduce best statistical practices to undergraduate biology majors?
We need new tools to start teaching best practices from day one.
Is 50:50 an appropriate null model for measuring gender bias? Ecologists should know better
Ecologists use null models every day. But we rarely use them when measuring gender bias in academia.
Ecologist Spotlight: Cecilia O’Leary
We seek out ecologists with diverse backgrounds and perspectives to highlight their work and share their stories and experiences. Check out this week’s Ecologist Spotlight featuring Cecilia O’Leary!