In 1925, the American entomologist Walter Sidney Abbott proposed an equation for assessing efficacy, and it is still widely used today for analysing controlled experiments in crop protection and phytomedicine. Typically, this equation is applied to each experimental unit and the efficacy estimates thus obtained are then used in analysis of variance and least squares regression procedures. However, particularly regarding the common assumptions of homogeneity of variance and normality, this approach is often inaccurate. In this tutorial paper, we therefore revisit Abbott’s equation and outline an alternative route to analysis via generalized linear mixed models that can satisfactorily deal with these distributional issues. Nine examples from entomology, weed science and phytopathology, each with a different focus and methodological peculiarity, are used to illustrate the framework.