On 14 Feb 2002 17:14:24 -0800, [EMAIL PROTECTED] (Thomas Souers) wrote: TS> > I have another question regarding one-way ANOVA. I have noticed > that in some books, nothing is said about what you can do when the > factor level variances are unequal. In Neter's big book, > transformations are recommended. "
Well, there are a lot of excuses for comparing *two* means. It is tougher to make up reasons why you ought to compare more than two, when they are arbitrary sets of numbers that are not well-behaved. For instance, they are *potentially* well behaved, in my book, if they simply happen to have been recorded or measured in the wrong units/ scale -- so they will be fixed by transformation. You probably ought to be re-thinking your whole scientific hypothesis and test, if your problem is worse than that. TS> > If the data are approximately normal, why not just use a > Satterthwaite approximate t-statistic for pairwise comparisons? > For example, you could use a Bonferroni type procedure. > What are people's opinions about this approach?" You can see my comments (today) on another thread, about t-tests. If Ns are equal, it doesn't matter which test. So you might as well use the regular apparatus. If they are not, both tests are fairly rotten by one-tailed criteria. By the way: What clinical research uses in followup testing for unequal N is either Bonferroni correction, or one or another *approximation* (which may not be very good). (I think I would never trust 'exact procedures' that may have been designed for unequal N, generically.) Personally, I try to do important tests and avoid Bonferroni. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =================================================================
