Hello. I have come across a curious result that I cannot explain. Hopefully, someone can explain this. I am doing a 1-way ANOVA with 6 groups (example: summary(aov(y~A)) with A having 6 levels). I get an F of 0.899 with 5 and 15 df (p=0.51). I then do the same analysis but using data only corresponding to groups 5 and 6. This is, of course, equivalent to a t-test. I now get an F of 142.3 with 1 and 3 degrees of freedom and a null probability of 0.001. I know that multiple comparisons changes the model-wise error rate, but even if I did all 15 comparisons of the 6 groups, the Bonferroni correction to a 5% alpha is 0.003, yet the Bonferroni correction gives conservative rejection levels.
How can such a result occur? Any clues would be helpful. Thanks. Bill Shipley Associate Editor, Ecology North American Editor, Annals of Botany D�partement de biologie, Universit� de Sherbrooke, Sherbrooke (Qu�bec) J1K 2R1 CANADA [EMAIL PROTECTED] <http://callisto.si.usherb.ca:8080/bshipley/> http://callisto.si.usherb.ca:8080/bshipley/ [[alternative HTML version deleted]] ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
