On Sun, Jun 8, 2008 at 12:58 PM, Douglas Bates <[EMAIL PROTECTED]> wrote: > On 6/7/08, John Fox <[EMAIL PROTECTED]> wrote: >> Dear Dieter, >> >> I don't know whether I qualify as a "master," but here's my brief take on >> the subject: First, I dislike the term "least-squares means," which seems to >> me like nonsense. Second, what I prefer to call "effect displays" are just >> judiciously chosen regions of the response surface of a model, meant to >> clarify effects in complex models. For example, a two-way interaction is >> displayed by absorbing the constant and main-effect terms in the interaction >> (more generally, absorbing terms marginal to a particular term) and setting >> other terms to typical values. A table or graph of the resulting fitted >> values is, I would argue, easier to grasp than the coefficients, the >> interpretation of which can entail complicated mental arithmetic. > > I like that explanation, John. > > As I'm sure you are aware, the key phrase in what you wrote is > "setting other terms to typical values". That is, these are > conditional cell means, yet they are almost universally misunderstood > - even by statisticians who should know better - to be marginal cell > means. A more subtle aspect of that phrase is the interpretation of > "typical". The user is not required to specify these typical values - > they are calculated from the observed data. >
How does Searle's "population marginal means" fit in to this? The paper describes a PMM as "expected value of an observed marginal mean as if there were one observation in every cell." - which was what I thought happened in the effects display. Is this a subtly on the definition of typical, or is that PMM's are only described for pure ANOVA's (i.e. no continuous variables in model)? Hadley -- http://had.co.nz/ ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.