On Thu, 14 Feb 2002 23:48:02 +0100, "Matthias" <[EMAIL PROTECTED]> wrote:
> Hello, > > would be nice if someone can give me some advice with regard to the > following problem: > > I would like to compare the means of two independent numerical sets of data > whether they are significantly different from each other or not. One of the > two underlying assumption to calculate the T-Test is not given (Variances > are assumed to be NOT equally distributed; but data is normally > distributed). What kind of (non?)parametric-test does exist - instead of the > T-Test - to calculate possible differences in the two means? [ ... ] The *logical* or measurement problem raised by 'different variances' is manifested when one sample predominates at both extremes. In that case, a conclusion about 'superiority' depends on someone's scaling or weighting of scores. That problem does not exist when the difference between groups is a shift of the mean, or a stretching of the distribution to one side. Comparing *means* ... Are you sure that you want to focus on means? Then it might as well be the t-test, evaluated one way or another: equal variances-assumption; unequal; or randomization. Other than means: The problems that lead to 'other tests' are ones that say the means are 'meaningless', and that you want to look at some version of stochastic superiority. But if the shapes are similar (same family), then the t-test with equal Ns is accurate; and with vastly unequal Ns, the two standard tests are both biased and potentially misleading -- so you have to look at both, and decide whether you should prefer one over the other based on (for instance) where and how the data were collected, or how they arise. If the shapes of distributions are not similar, then rank-transformation is not reliable or robust for 'superiority.' You can compute some Robust tests, such as the 2x2 contingency test, which may be based on median split or whatever split meets your needs. -- 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/ =================================================================
