Ah, I see where we are talking past each other. In my particular analysis (I'm looking at deviations from a predicted value), any deviation from 0 (whether due to grand mean or not) is actually very very interesting. What is ultimately interesting to me is the sign of that difference, but, I need to establish any difference at all first. The model I should actually be working with is more like lm(response ~ trta*trtb+0), really. But, still, in evaluating the glht output, is it fair to use the 48 df, or should I use the df for each cell? I think that's where I've been getting hung up.
Chuck Cleland wrote: > > On 3/5/2008 3:19 PM, jebyrnes wrote: >> Indeed, but are not each of the cell means also evaluations of the effect >> of >> one factor at the specific level of another factor? Is this an issue of >> "Tomato, tomahto". > > I don't think it is "tomato, tomahto". Say the grand mean is around > 100 and the within cell standard deviations are around 10. You could > easily have a situation in which all of the cell means are significantly > different from 0, but there is nothing at all interesting going on with > the two explanatory factors. In other words, the cell means can be very > different from 0 with no explanatory variable effects of any kind, based > only on the overall location of the response. > >> I guess my question is, if I want to know if each of those is different >> from >> 0, then should I use the 48df from the full model, or the 9 for each >> cell? > >> Chuck Cleland wrote: >>> That does not corresponds to what I think of as the simple effects. >>> That specifies the six cell means, but it does not *compare* any cell >>> means. I think of a simple effect as the effect of one factor at a >>> specific level of some other factor. >>> >>>> summary(glht(fm, linfct = cm2), test = adjusted(type="none")) >>>> >>>> Correct? What is the df on those t-tests then? Is it 48? >>> Yes, df = 48 for each contrast. >>> >>>> Interestingly, I find this produces results no different than >>>> >>>> fm2<-lm(breaks ~ tension:wool+0, data=warpbreaks) >>>> summary(fm2) >>> Yes, but those are not what I would call the simple effects. Those >>> are essentially one-sample t-tests for each of the 6 cell means. >>> >>>> Also, here, it would seem each t-test was done with the full 48df. >>>> Hrm. >>> The df are based on the whole model, not the 9 observations in one >>> cell. > > -- > Chuck Cleland, Ph.D. > NDRI, Inc. > 71 West 23rd Street, 8th floor > New York, NY 10010 > tel: (212) 845-4495 (Tu, Th) > tel: (732) 512-0171 (M, W, F) > fax: (917) 438-0894 > > ______________________________________________ > 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. > > -- View this message in context: http://www.nabble.com/Asking%2C-are-simple-effects-different-from-0-tp15835552p15877383.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
