Hi Robert, Thank you for your reply, and for what appears to be some good/sound practical advice on managing this kind of problem.
Best Regards, Mark. Robert A LaBudde wrote: > > Statistical significance is "detectability", and depends upon the > size of the sample as well as the effect. A large enough experiment > will result in statistical detectability of almost every interaction > action term allowed. > > This is why estimation, not testing, has become the consensus > recommendation in statistics. > > As a practical matter, evaluate the combined effect of your model > terms with and without the interaction term(s) you are worried about. > Is the reduction in accuracy of physical importance? If so, the > interaction terms are required for scientific reasons. If not, > present both results and indicate the acceptability (for > interpolation) of the simpler model. > > You should also make it your first priority to hypothecate why the > interaction terms are meaningful and expected. If a cause can be > found, it may suggest an alternate model that will eliminate > interactions, or satisfy your anxiety. If not, it may support your > argument to simplify. > > > At 08:58 AM 7/21/2007, Mark wrote: > >>Dear List Members, >> >>I would very much appreciate any pointers you could give me on the following >>matter: >> >>Main Question: >>To what extent does the "rule" that it is unreasonable to talk about main >>effects if there are significant interactions in a model depend upon effect >>size [of the significant interaction terms]? Or is this not an issue? >> >>More practically: Suppose I were to carry out a so-called Type-II MANOVA >>(using ffmanova) and were to find that the interaction term in a 2-way >>analysis has borderline significance (say p = 0.045) and a small effect >>size, whereas one of the main effects is highly signficant (say p = 6.8e-10) >>and has a large effect size. >> >>Would it in this case be reasonable for me to ignore the interaction term, >>and talk only about main effects? And, presuming the main question is fair, >>are there general guidlines concerning the relationship between level of >>significance and effect size for interaction terms. >> >>Thank you in advance for your help, > > ================================================================ > Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: [EMAIL PROTECTED] > Least Cost Formulations, Ltd. URL: http://lcfltd.com/ > 824 Timberlake Drive Tel: 757-467-0954 > Virginia Beach, VA 23464-3239 Fax: 757-467-2947 > > "Vere scire est per causas scire" > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > -- View this message in context: http://www.nabble.com/Effect-size%2C-interactions%2C-and-main-effects-%28Stats-Question%29--ffmanova--tf4121771.html#a11723512 Sent from the R help mailing list archive at Nabble.com. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
