Disclaimer: I am in the process of teaching myself mixed effects modeling, so apologies if I've not conceptualized part of the process properly. I am attempting to model change in blood antigen levels over time vs. infection status for patients undergoing a certain therapy, using proc mixed. I have blood levels at baseline (t = 0) and at several different time points after initiation of therapy. I also have infection status at each of those time points (infection/no infection), and that status can change over time. It is my understanding that, in general, it may be potentially usefully to include the intercept as a random effect (i.e. different intercept for each subject) when searching for the 'best' model. I'm my case however, since I have the baseline measurements, I already know the intercepts for each patient. Is there any way for me to make sure these values are included in the model? Does using the noint option accomplish this? Are there other procs that might allow me to manually specify the intercepts? On a related note, how does one interpret the effect of infection on antigen levels, when infection status can change over time? Is it simply a matter of never infection vs. any infection? Thanks, Andrew
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