Hello everybody,

I'm desperately searching for some help. I'm currently studying the example of a Mixed Anova presented by Andy Field in his book "Discovering Statistics Using R". The example is decribed here: https://en.wikipedia.org/wiki/Mixed-design_analysis_of_variance. Suprisingly, I have no problems when it comes to replicating his steps in R, but I do not understand the mathematical background of this Anova. Is it a 2x3x3 design? (2= gender, 3=factor personality (high, average, low), 3=looks (high, average, low) Or am I completely wrong and it's something different? And concerning a "two-factor Anova with repeated measurement on both factors", in this case, I am missing that the participants are also grouped by gender, so I can not use the literature on this one, right?

Thank you very much in advance!


Ps. Please excuse my bad English :)


Active Member
What R function is Field using to do the analysis? Can you type out the function call so that I can see the model?

I find it bizarre that the author of the wikipedia article calls within-subjects factors "random factors." I don't recall ever having seen the term used that way. It would imply in the Field example that personality and looks are random factors. To my way of thinking (and that of everyone else, as far as I know), these (along with gender) are fixed factors: they have a limited number of levels, they are the only levels of interest, and they can't be interpreted as a random sample from a population. The random factor in the Field example is the subject (or "block" in the classical literature): they are a sample from a larger population to which inferences are to be made. Thus the Field model has four main effects: subject, gender, personality, and looks. Subject is a random factor; the others are fixed factors.
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