I�m running a mixed model analysis with 2 fixed factors that are intercorrelated using the lme function and I�m having difficulties in interpreting the results. As I�m quite novice I�ll try to use a very simple example.
My model is lme(Y~A*B). A has 3 levels (1, 2 and 3) and B has 2 levels (I and II). My results are something like this: P statistic B:II P=0.01 A:2 P=0.01 A:3 P=0.09 II*2 P=0.61 II*3 P=0.031 My question is as follows. I understand that R keeps a level of each factor and reports any statistical differences to it. So in this example it reports that II is different than I and 2 against 3. However when it comes to the intercorrelation, what does it report? Does it compare II*2 and II*3 to II*1 and if so what happens with I*2 and I*3? Or does it compare II*2 to I*2 and II*3 to I*3 and if so what happens to I*1 and II*1? Thank you Vasillis [[alternative HTML version deleted]]
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