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IdahoAgStats · Jul 24, 2024 · 29474e0 · 29474e0
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 # Mixed model theory and background
 
-Mixed-effects models are called “mixed” because they simultaneously model fixed and random effects. Fixed effects (e.g. treatments) represent population-level (i.e., average) effects that should persist across experiments. Fixed effects are similar to the parameters found in “traditional” regression techniques like ordinary least squares. Random effects are discrete units sampled from some population (e.g. plots, pariticipants), they are inherently categorical (Winter, 2019).
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+Mixed-effects models are called “mixed” because they simultaneously model fixed and random effects. Fixed effects (e.g. treatments) represent population-level (i.e., average) effects that should persist across experiments. Fixed effects are similar to the parameters found in “traditional” regression techniques like ordinary least squares. Random effects are discrete units sampled from some population (e.g. plots, participants), they are inherently categorical (Winter, 2019).
 
 #### Model