Some time ago a PhD student of mine needed to conduct simple main effects for several different ANOVA designs. As the explanation of how to do this is a bit fiddly (and it is the kind of thing I get asked about quite a lot) I decided to write the explanation down. This later turned into a web page and now I'm updating it for this blog. The main focus is on explaining how to do the calculations based on output from generic ANOVA software. The calculation methods I describe seem obvious to me, but intended to be the best or most efficient method. Rather, their aim is to make clear what the calculation is doing and to be sufficiently robust that one can adapt them to most (if not all) standard ANOVA software.

Until relatively recently most psychologists had never heard of sphericity. Most text books didn't mention it (and even now some of them confuse it with compound symmetry). The big change happened a few years ago when SPSS started including information about sphericity in its repeated measures ANOVA output. Of course, because most undergarduate text books didn't mention it people started looking for information on it.

I've no idea.

Some time ago I had the idea of a blog about the kinds of statistics I use in my work. I didn't really think much about it until I noticed a couple of blogs by a friend of mine (Learning Statistics and Applying Regression by Jeremy Miles). Jeremy's blogs pointed me to the excellent Statistical Modeling, Causal Inference and Social Science by Andrew Gelman and Samantha Cook.
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