On Thu, Mar 4, 2010 at 9:03 AM, S Ellison <s.elli...@lgc.co.uk> wrote: > > >>>> "John Fox" <j...@mcmaster.ca> 02/03/2010 02:19 >>> >>There's also a serious question about whether one would >>be interested in main effects defined as averages over the level of > the >>other factor when interactions are present. > > My personal take on this particular chestnut is that I often want to > ask something about the relative size of the effects. If the so-called > "main effect(s)" is/are very much larger than the interactions, one may > be able to make generalisations which have practical use.
Sure. But if there is an interaction, main effect generalizations are going to be less precise than generalizations based on simple effects. I agree that there are some situations in which it makes sense to ignore a small but significant interaction, but I think this should be a rare exception to the rule "don't interpret main effects in the presence of an interaction". -Ista If the effects > are much of a size, there's nothing much to be gained by asking about > "main effects". > > Mind you, that's probably a crit of significance testing as the be-all > and end-all, rather than a problem with type I-III. Asking 'how big is > it?' is a step beyond 'is it there?'. > > Steve E > > ******************************************************************* > This email and any attachments are confidential. Any u...{{dropped:18}} ______________________________________________ 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.