I am using a three-level mixed-effects model in which:
- individuals (level 1) are nested in
- primary sampling units (PSUs) or enumeration areas (level 2) which in turn are nested in
- countries (level 3).
xtmixed command I get fixed effects for all my variables in standard regression coefficients and random effects for countries and PSUs as a sum of variance and co-variance parameters.
- If my random-effects parameters are for
0.192*** (SE 0.030)and for
0.620*** (0.020), how do I interpret them?
- Should I just report what proportion of the variance is at the PSU level and at the country level?
- Do these random-effects parameters say anything about the fixed-effect regression coefficients?
- Can these parameters be used to predict the intercept of the DV?
- Looking at the random-effects parameters can I justify my mixed-effects model building?