I sat up a mixed-effects linear model with the dependent variable log-transformed (in oder to get it normal distributed and as ist is common with this kind of data in other publications). All fixed affects are significant and a consequent multiple comparissons of means works also great (significant differences of log10 values of different treatments). Now I wonder how to interpret the model estimates quantitatively. It seems not correct to just re-transform the estimates. Although the results are in the regular range and the means are in the same order as with untransformed values. [Only related topic I found is this] but I'm not sure if it is applicable to my case. The formula I use is:
log10(y) ~ = 0 + var1:var2 + var1:var2:cov1 + var1:var2:cov2
I'm working with R btw. Thanks for any help.