Estimating Precision, Repeatability, and Reproducibility From Gaussian and Non-Gaussian Data: A Mixed Models Approach

Quality control relies heavily on the use of formal assessment metrics. In this paper, for the context of veterinary epidemiology, we review the main proposals, precision, repeatability, reproducibility, and intermediate precision, in agreement with ISO (International Organization for Standardization) practice, generalize these by placing them within the linear mixed model framework, which we then extend to the generalized linear mixed model setting, so that both Gaussian as well as non-Gaussian data can be employed. Similarities and differences are discussed between the classical ANOVA (analysis of variance) approach and the proposed mixed model settings, on the one hand, and between the Gaussian and non-Gaussian cases, on the other hand. The new proposals are applied to five studies in three diseases: Aujeszky’s disease, enzootic bovine leucosis (EBL), and bovine brucellosis. The mixed-models proposals are also discussed in the light of their computational requirements.