Hi everybody,

I have a crossover study 2x2 design with 2 treatments and 2 baselines. Each phase consisted of one measurement before treatment (pre or baseline) and one after treatment (post). The data table looks like this:

Subject | Sequence | Phase | Treatment | Time
   1         AB        1         A        pre-baseline     
   1         AB        1         A        post     
   1         AB        2         B        pre-baseline      
   1         AB        2         B        post     
   2         BA        1         B        pre-baseline
   2         BA        1         B        post
...

I'm really not sure about the formula i should use to compare the effect of treatments at final time point (post), controlling for baselines and also for the "Sequence" variable (as my PCA shows distinct separation based on this variable). I went through the vignette but didn't find any example with such a design, does somebody have an idea?

Any help would be greatly appreciated!

You would do it the same as you would approach it with lm(), there are lots of posts online if you search for how to use linear models to approach this. Otherwise, I'd recommend consulting with a statistician, unfortunately I'm not in a position where I have sufficient time to work out designs, but have to reserve my time for software related support here.