It’s surprisingly common for biologists to combine crossed and nested factors. These designs are partly nested or split-plot designs. They are nearly always mixed models, usually a random nested effect and at least two fixed effects. We describe the analysis of these designs, starting with a simple three-factor design with a single between-plot and a single within-plot effect, extending this analysis to include multiple effects, including interactions at this level, and adding continuous predictors (covariates).
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