for my master thesis i worked with mixed linear models for the first time. I am trying to get results concerning the effect of tree ring width on various wood anatomical features of two different tree species. I formulated my model in R like this:
> lmer(CD.~scale(MRW)*species+(1|ID)+(1|Year), data= Alles4)
CD. being an anatomical feature,
MRW the tree ring width,
ID the individual tree and
Year the year of tree ring formation. Species is a categorical variable with only the two tree species.
I got the following results:
Fixed effects: Estimate Std. Error df t value Pr(>|t|) (Intercept) 222.9791 4.9012 37.6322 45.494 < 2e-16 *** scale(MRW) -16.2370 0.7431 2373.4519 -21.850 < 2e-16 *** speciesS -22.8443 6.7561 34.0283 -3.381 0.00183 ** scale(MRW):speciesS 4.1713 0.9364 2352.8566 4.455 8.79e-06 ***
I think I am clear in the understanding of the fixed effects by themselves, however the interpretation of the interaction between these two I am not sure about. I understand that there is a significant interaction, but how do I report it?
At species=1 each step of MRW decreases CD. by 16,2370? So at species=2 each step of MRW decreases CD. by 16,2370-4,1713=12,0657, hence CD. of species 1 is more effected by MRW than CD. of species 2 and this effect is significant?