Hi, I am trying to fit a ANCOVA model using lmRob. The P-values of the variables in the model differ hugely between the summary() function and the anova() function (from >0.8 in the summary to <0.001in the anova for the same variable). I understand that with an ANCOVA the order in which the variables are added to the model matters and that this influences the P-value, but can this make such a big difference? Which P-values are best to use? Also, could this be an indication something is wrong with my model? Any help would be greatly appreciated! Thanks, Geertje ~~~~ Geertje van der Heijden PhD student Tropical Ecology School of Geography University of Leeds Leeds LS2 9JT Tel: (+44)(0)113 3433345 Email: g.m.f.vanderheijden04@leeds.ac.uk [[alternative HTML version deleted]]
Geertje Van der Heijden wrote:> > Hi, > > I am trying to fit a ANCOVA model using lmRob. The P-values of the > variables in the model differ hugely between the summary() function and > the anova() function (from >0.8 in the summary to <0.001in the anova for > the same variable). I understand that with an ANCOVA the order in which > the variables are added to the model matters and that this influences > the P-value, but can this make such a big difference? > Which P-values are best to use? Also, could this be an indication > something is wrong with my model? >Someone may know the answer to this off the top of their head, but if you provided a reproducible example you would be much more likely to get an answer ... Ben Bolker -- View this message in context: http://www.nabble.com/Question-about-lmRob-tf4822281.html#a13809917 Sent from the R help mailing list archive at Nabble.com.