Advanced data processing

Generalized linear mixed models + methodology and experimental protocols to account for biological reality: non-normal distribution and pseudo-replication

Protocol optimization, power, and uncontrolled type I risk: variable transformation, polynomial regression, link function, likelihood, model selection

Deviance and goodness-of-fit analysis

Incorporation of blocks, repeated measurements over time, consideration of spatial and temporal correlation, over-dispersion

Graphical representation of predictions.

Taking biological complexity into account in analyses and their graphical representations.

Mastery of linear models with multiple explanatory variables (EVA)

Continuous assessment: 100%