I'm running a simple ACE model of a continuous variable in openMX. I'm running both a constrained and sex-limited model to see which provides a better fit, and then running various constrained or sex-limited submodels where a or c are dropped.
Here is what I have noticed -- in a sex-limited submodel where c is dropped, the a and e variance components and confidence intervals are extremely similar across males and females -- AND, extremely similar to the components for a constrained model where c is dropped.
However, the sex-limited model is a SIGNIFICANTLY better fit. There is no comparison. It's waaaaay better, and yet, in reporting the variance components, it looks like it's about equal to the constrained model that's more parsimonious.
I'm having trouble wrapping my mind around this conceptually. Anyone have any insights? Would it be helpful to post my syntax?