Hello,
I am fitting a piece-wise linear mixed model with a random change-point, very similar to the model in this topic: Piecewise Linear Mixed Models With a Random Change Point. In my model, the first slope (slope1), change-point (knot) and Intercept are the random effects.
However, my model is struggling to fit when I allow the correlation between all random effects to be estimated, using:
Intercept + slope1 + knot ~ 1 + (1|a|subjid)
I would therefore like to investigate pairwise combinations of correlations. For instance, how do I allow for correlation between the Intercept and slope1 as well as between slope1 and knot but not allow for correlation between Intercept and knot? I.e. I want to constrain the correlation between Intercept and knot to be 0 but allow the other two correlations to be estimated. I tried the following code but (unsurprisingly) it did not do what I wanted:
Intercept + slope1 ~ 1 + (1|a|subjid),
knot + slope1 ~ 1 + (1|b|subjid)