I concur. I should have said "if TI used that approach it might explain the small differences in the results."
Art Rich Ulrich wrote: > posted and e-mailed. > > On Mon, 06 Jan 2003 22:29:56 GMT, "Arthur J. Kendall" > <[EMAIL PROTECTED]> wrote: > > [ ... ] > >>It looks as if the TI is using about 8.1 df. (or the harmonic mean of >>[10,7] ) which gives fractional df. >> > > I think you nailed that one. > >>Since one SD is twice the other, the Levene F for non homogeneous >>variances is about 4. So the "separate variance" interval estimate >>would be more appropriate and would result in small differences. >> > > > - of course, you are not supposed to make the choice of > test on this ad-hoc basis. > > To be more explicit: according to a couple of > articles that I read (and I agreed on this point), it is a BAD > practice to 'condition' your choice. You are not > supposed to let the test of variances determine > which t-test to believe. > > For equal Ns, the difference in tests is *very* slight. > For unequal Ns, both the versions of t-tests mis-behave > rather badly in their one-tail rejection rates. The > separate-variance tests (there are a couple of versions) > are minimally more robust than the Students t, but not > enough (in my opinion) to justify favoring them. > - Insist on both tests showing the same, or consider > transformations. Your "best test" will come if you find > the transformation that is both logical and normalizing. > A rank order transformation (non parametric test) is > usually available and convenient, and almost as good. > . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
