Hi All

I'm running two linear spline mixed-effects models (growth curve analysis) looking at mental health and BMI development over time (models include 4 splines for 4 time periods):

for mental health:
Code:
 
 eststo: mi estimate, post: mixed mh age10_16 age16_23 age23_33 age33_42 || id: agec, cov(unstr) mle stddev
for BMI:
Code:
 
 eststo: mi estimate, post: mixed bmi age10_16 age16_23 age23_33 age33_42 || id: agec, cov(unstr) mle stddev
The above models run well.

I would now like to predict the individual-level intercepts and slopes for mental health & BMI generated by the above two models as I plan to run further linear regressions between them.

So, I would have mental heath slope and intercepts variables and BMI slope and intercepts variables (generated from the spline models above) to run a regular linear regression like:

regress bmislope mentalhealthslope bmi-intercept mh-intercept

Running, for mental health:
Code:
 
 predict mh
only gives me the average slopes for the four splines (i.e. all individuals have the same set of four slopes) and not the individual level slopes that I would like to have. I would I obtain these?

Thanks!
/Amal