Robust inference and errors in studies of wildlife control

Abstract

Abstract Randomized, controlled trials (RCT) are seen as the strongest basis for causal inference, but their strengths of inference and error rates relative to other study have never been quantified in wildlife control and rarely in other ecological fields. We simulate common study designs from simple correlation to RCT with crossover design. We report rates of false positive, false negative, and over-estimation of treatment effects for five common study designs under various confounding interactions and effect sizes. We find non-randomized study designs mostly unreliable and that randomized designs with suitable safeguards against biases have much lower error rates. One implication is that virtually all studies of lethal predator control interventions appear unreliable. Generally, applied fields can benefit from more robust designs against the common confounding effects we simulated.