Rich Ulrich <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>... > On Wed, 26 Feb 2003 16:01:25 -0600, "DCD" <[EMAIL PROTECTED]> wrote: > > > I have collected some data using older adults have found a significant > > difference (p < .05) between the three groups in terms of their activity > > level. Subsequent to this analysis I am contrasting the three groups on a > > balance measure and deciding whether or not to use activity level as a > > covariate in the ANOVA calculations. > > There is a DIFFERENCE measured between groups in Activity; > and you want subsequently wonder whether to use activity > level as a covariate. > > Well, if it has a logical role as a covariate, then you might > *have* to try it as a covariate, or else concede whatever > arguments someone makes about it. Those could be strong > arguments if it is strongly correlated. > > However, having mean-differences on a covariate is always > problematic -- you really do, basically, *have* to plot the > means and scores to see who is being affected. Are there > ceiling/ basement effects? Do regression lines cross? > Is regression-to-the-mean sufficient to explain everything > that is otherwise interesting? > > On the other hand, if you stick in the covariate and it > makes no difference that is discernible on any test, > then you can say *that* about it. > > > > > > The question I have is whether or not to use activity level as a covariate > > or not, based on the fact that the main effect for activity level violated > > the assumptions of the homogeneity of regression slopes when compared with > > one of the DV used in the study. > > - There are mean difference, *plus*, somewhere else, you see > violations of homogeneity? - well, the heterogeneity (if there > is any on this variable) is potentially less important than the > difference in means. I should say, when I see the logic misused, > I do wonder whether the underlying facts have been grasped. > > You can't write an adequate argument, in a non-randomized > study (which this apparently is) if you leave out *any* factor that > other people will find interesting or important. > So, I think you *have* to look at this potential covariate to > see what it is doing. It might be that the most important thing > to announce might be, that it is badly distributed, or badly > *confounding* the other variables; and you need help to > figure it out further. > > > I do have a small sample size and > > consequently did not use the covariate analysis but wanted to see if I was > > justified based on the violation listed above. > > > > Any help would be appreciated. > > You can try to *discount* some analysis based on > troubles with the scores. But for an observational study, > that is the practically equivalent to admitting defeat, if someone > has other ideas about that variable.
Bruce - Sorry, but I mistakenly attributed something to you that I had meant to attribute to the original requestor. Sorry about that. Jim . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
