Hello,
I have a relatively large dataset (500 same sex twin pairs) where the raw correlations of the observed phenotypes between MZs and DZs show shared environment effects (e.g., MZ-.39 vs. DZ-.29). Moreover, if I enter only these correlations into a script in the old Mx program, I get significant shared environment effects.
Nevertheless, when I built the script in openMx and did model comparisons, the AE model was not significantly worse than the ACE model, suggesting that it is better to adopt the AE, and not the ACE model. Similarly, the CE model was not significantly worse than the ACE model. Only the E model was significantly worse.
I would like to ask two questions in that matter:
1) In general, when E is worse than ACE, but CE and AE are not worse than ACE, which model is the best model and what should I conclude from such results?
2) what could be the statistical/ theoretical reasons not to find shared environment effects in the openMx method of models comparison, although the raw data indicates that there are such effects?
Thank you very much