I am studying the heritability of a variable by utilizing the ACE model, and would like to ask the OpenMX community if i am analyzing my results correctly.
When i run the ACE model, followed by the AE and CE models, i get the following results for 2 different datasets:
COMPARE ALL MODELS: Print Comparative Fit Statistics
(Nested.fit <- rbind(
mxCompare(SatFit, AceFit),
mxCompare(AceFit, AEFit)[2,],
mxCompare(AceFit, CEFit)[2,]))
Dataset 1
Model A (95% CI) C (95% CI) E (95% CI) (-2LL) df AIC ∆-2LL ∆df p-value
ACE 43.68% (0.15 - 0.69) 17.18% (0 - 0.39) 39.15% (0.3 - 0.5) 4869.562 16483 -28096.44 8.57 0.07
CE (-) 48.08% (0.4 - 0.55) 51.92% (0.45 - 0.6) 4878.036 16484 -28089.96 8.47 1 0
AE 63.84% (0.55 - 0.72) (-) 36.16% (0.28 - 0.45) 4871.678 16484 -28096.32 2.12 1 0.15
Dataset 2
Model A (95% CI) C (95% CI) E (95% CI) (-2LL) df AIC ∆-2LL ∆df p-value
ACE 39.2% (0 - 0.61) 9.73% (0 - 0.48) 51.07% (0.39 - 0.65) 1884.466 2668 -3451.53 11.45 0.02
CE (-) 42.3% (0.36 - 0.53) 57.7% (0.47 - 0.69) 1887.154 2669 -3450.85 2.69 1 0.1
AE 49.83% (0.37 - 0.61) (-) 50.17% (0.38 - 0.63) 1884.668 2669 -3453.33 0.2 1 0.65
I just want to ask if my interpretation of the data (below) is correct:
For Dataset 1, removing A (genetics) from the model gave a p-value of 0, meaning that its presence is significant. Removing C (shared environment) however gave a p-value of 0.15, meaning that removing this factor did not have any significance on the model. In conclusion, seeing that removing the C factor proved insignificant, my variable of interest has a heritability of about 63.84%.
With respect to Dataset 2, the p-values for all except the ACE model were insignificant.
Is this interpretation correct?
I am confused as to whether i should just look at changes in p-value alone, AIC measures, or whether i should be analyzing these results in another way.
Thank you very much.