Mixed Models Offer No Freedom from Degrees of Freedom

Abstract

Statistics matter greatly in biology, whether we like it or not. As a discipline with an empirical inclination, we are faced with data every day and we rely on inferential statistical models to make sense of it and to provide us with novel insights. Much of the time, the growing level of complexity and sophistication of the models we put to use in ecology and evolution have led to more appropriate analyses of our data. However, this is not always the case. Here, I draw attention to a classic flaw in inferential statistics that has resurfaced in a new flavor as a result of increased reliance on complex linear mixed models - the multifaceted and disturbingly persistent problem of pseudoreplication.

Keywords: biostatistics; experimental evolution; hierarchical data; linear mixed models; pseudoreplication; type I errors.