Hey Bob, yes, if you sum-code (aka contrast code) the main effects, the way you describe it below, you will be all set (at least for balanced data; for unbalanced data, you may want to center the variable). The interaction just multiplies the value of the two main predictors (leading to the values you give below), and -for balanced data- the interaction should be orthogonal to the main effects. The fitted coefficients will indeed differ from the default dummy coding (which is 0 vs. 1 coding, which is *not* centered).
HTH, Florian On Fri, Sep 5, 2008 at 4:27 PM, Bob Slevc <[EMAIL PROTECTED]> wrote: > Hi there R-language-gurus, > > I have what I think is a simple question – maybe even a stupid question > (and there are too stupid questions) – that's related to recent discussions > on this list. Imagine, if you will, that I have a full-factorial design, > and want to set up a set of orthogonal contrasts rather than using R's > default dummy coding. For a simple 2x2 design, I want something like this, > where contrasts 1 and 2 are the main effects for A and B, and contrast 3 is > the interaction: > > a1 a1 a2 a2 > b1 b2 b1 b2 > contrast1 1 1 -1 -1 > contrast2 1 -1 1 -1 > contrast3 1 -1 -1 1 > > I haven't found any contrast function (e.g., contr.poly / contr.sum / etc.) > that'll automatically create a matrix for this kind of contrast, but can I > just specify the individual factor contrasts and assume that R will just > multiply them to give nice orthogonal interaction contrasts? For example, > if my factors are called A and B, and I say: > > contrasts(datafile$A) <- c(1,-1) > contrasts(datafile$B) <- c(1,-1) > > and then run a model (on log(RTs) apparently): > > model <- lmer(log(RT) ~ A*B + (1|subj) + (1|item), data=datafile) > > Then am I set? I'm a little unsure, partially because it gives me slightly > different results than the default dummy coding does (though it does seem to > be orthogonal as the correlations between fixed effects are all zero...) > > Thanks much, > Bob > > --- > L. Robert (Bob) Slevc, Ph.D. > Rice University, Dept. of Psychology • 6100 Main Street • Houston, TX 77005 > http://www.ruf.rice.edu/~slevc/ <http://www.ruf.rice.edu/%7Eslevc/> > > > _______________________________________________ > R-lang mailing list > [email protected] > http://pidgin.ucsd.edu/mailman/listinfo/r-lang > >
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