The importance of being random! Taking full account of random effects in nonlinear sigmoid hierarchical Bayesian models reveals the relationship between deadwood and the species richness of saproxylic beetles

Hierarchical models are used to study the relationship between a response variable and a predictor in structured data. Random effects are meant to capture the structured part of variability among groups of observations. In ecology, random effects are usually incorporated into the intercept. Their application to the other parameters of the curve, especially in nonlinear curves, has been understudied. However, applying random effects to different...