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1-0 (cheat org) has rated this game with a score of 4.4/5.0. To see a detailed breakdown of user and critic scores for this game click here.Q:
Constant part of mixed model ANOVA applied to one of its predictor components
I want to do an ANOVA on the dependent variable $y$ in the presence of the predictors $x_1$ and $x_2$. I want to perform a partial split-plot design in which both predictors are evaluated at different treatments:
$\mathrm{Set}$ for $x_1$ and
$\mathrm{Sow}$ for $x_2$
What is the constant part of the overall ANOVA model for this split-plot design? Since the predictors are themselves manipulated by experimental units, the reference level is probably each $\mathrm{Set} \times \mathrm{Sow}$ combination as a whole? So I would have
$$y \sim \mathrm{Set} \times \mathrm{Sow} + \epsilon$$
where the error term $\epsilon$ is random and normally distributed. The interaction term ($\mathrm{Set} \times \mathrm{Sow}$) contains the variation due to $\mathrm{Set}$ and $\mathrm{Sow}$ which I would be interested in. The treatment components $\mathrm{Set}$ and $\mathrm{Sow}$ are themselves manipulated by experimental units, i.e., they are crossed in my sample.
Is this model right? What do I do if I have the reference level to be the overall effect of the treatment (i.e., the full-split-plot design) instead? In that case, the reference level is $\mathrm{Set} \times \mathrm{Sow}$, rather than each set-by-sow combination, so I would have
$$y \sim \math
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