I am doing mixed model analysis to evaluate (Y=) fruit intake (continuous variable) between two groups (intervention versus control) over time (baseline, year 1, year 2, year 5, year 7 and year 15). My model look like this: Y = group + time + group*time. My question regards the baseline measurements. In my first analysis I was told to transform my data to a long format without the baseline measurements, and include this as a fixed effect to adjust for it. However, I then struggle as I have to interpret the results differently. If I include baseline data when I convert my data to long format,
Do I need to adjust for baseline - assume there are baseline differences between groups? I read somewhere that I don't need to adjust for baseline differences in mixed models with interaction terms.
Can I then include baseline measurements as a fixed effect or will this create collinearity?
My question is basically, how can I adjust for baseline measurements in mixed model analysis?