I hope you can help me with this question. I will try to explain my data:
I have a repeated measure design (with 16 measures at 'visit' 1 and 'visit' 2 for two groups: treatment and placebo). I am using linear mixed model before doing post-hoc testing(multiple comparisons). I have following variables:
Exhaled hydrogen (response variable) drink [treatment] (factor, fixed effect) Time (factor, fixed effect) visit (factor, fixed effect) Exhaled hydrogen at baseline (covariate, fixed effect)
The data are not normally distributed and therefore I did a log transfer.
My model looks like this:
hydrogen ~ drink*time+visit-1 + hydrogen_baseline, random=~1|participant, method="ML", data=breath, na.action = na.exclude)
My problem is that after the log transformation, the factor 'visit/treatment' is not significant anymore. Since I want to compare the effects after treatment, I am not sure how to deal with this problem.