Force model to go through 0 (repeated measures mixed model)

[Fabian Fortner]

Hi
I would appreciate your help regarding this issue in a observational study (medical field). Is there a way to force this model to go thorugh x=0 and y=0?

I want to model

1. the effect of a binary treatment variable: treatment
2. on a continuous outcome measure that starts at value = 0: measure
3. which is assessed repeatedly over time (time is continuous, not categorical): time
4. in multiple subjecs: subject_id

I did this using an approach like this:

mixed measure ///
           i.treatment##c.time_m##c.time_m ///   quadratic transformation
          || subject_id:

Then I create marginal predictions

margins  i.treatment, at(time = (0(1)9))
 
marginsplot, noci

Which results in this graph: However, as measure starts at =0 in reality, the fact that Treatment 2 start below 0 would seem odd to a reviewer or reader of the article. Is there a way to force this model to go thorugh x=0 and y=0? I thought about the noconstant option but this doesn't work.