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| From | John Antonakis <John.Antonakis@unil.ch> |
| To | statalist@hsphsun2.harvard.edu |
| Subject | Re: st: Why F-test with regression output |
| Date | Thu, 05 May 2011 00:05:55 +0200 |
Geary, R. C., & Leser, C. E. V. (1968). Significance Tests in Multiple Regression. The American Statistician, 22(1), 20-21.
Best, J. __________________________________________ Prof. John Antonakis Faculty of Business and Economics Department of Organizational Behavior University of Lausanne Internef #618 CH-1015 Lausanne-Dorigny Switzerland Tel ++41 (0)21 692-3438 Fax ++41 (0)21 692-3305 http://www.hec.unil.ch/people/jantonakis Associate Editor The Leadership Quarterly __________________________________________ On 04.05.2011 23:54, Joerg Luedicke wrote:
On Wed, May 4, 2011 at 5:19 PM, Steven Samuels<sjsamuels@gmail.com> wrote:Nick, I've seen examples where every regression coefficient was non-significant (p>0.05), but the F-test rejected the hypothesis that all were zero. This can happen even when the predictors are uncorrelated. So I don't consider the test superfluous.This is not surprising since "p>0.05" does not mean that the contribution of a predictor is zero. I cannot see an argument here why this F-test is not superfluous? I personally think that these kinds of omnibus significance tests are useless since they carry little information and thus little meaning. Say we have a model with 5 predictors, I want to see what each contributes in terms of effect sizes. If I see that all effects are essentially zero I can interpret that accordingly. What would it help if I looked at the F-test which does not even carry information about things like effect sizes etc.? I guess it is always printed out because it became standard at some point in time, and I believe especially in Psychology and experimental research. In Psychology, a common modeling strategy is to do an omnibus test first and if the null-hypothesis is rejected a more closer look is warranted. If not, the model gets discarded right away. J. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/
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