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Using the turbulence model, the (chi ^2) values are again approximately one.
(2008) model, the (chi ^2) values are clearly too small, particularly in case of the WHISP001 session ((chi ^2 < 0.5)), leading to an overestimation in these solutions.
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In order to check the proportional odds assumption of the model, the chi-square test was employed.
The results for model 2 that tested scalar invariance indicated a poorer fit compared to the previous model: the chi-square test of differences was significant, the BIC value was higher than the one obtained for model 1 and the ΔCFI was higher than.01.
Threshold of factor loading in this study is 0.32 [ 34] For this model, the chi-square statistic was 98.63 (degrees of freedom (df) = 38, N = 489), with the χ/df ratio having a value of 2.60.
Next, the model was re-estimated across each sustainability user and non-user sample, by constraining the path estimated to be equal (i.e., constrained model), revealing the Chi square value of 29.68 with df = 7.
For all three models, the chi-square statistic and the Akaike Information Criterion result to be much lower for the mixture model than for the other two.
To compare hierarchical models, the chi-square difference test was used.
Finally, for both models, the chi-square statistic of the contingency table which compared the number of "selected" females in each quartile of the EBV distribution in 2005 and 2006 was not significant (p > 5%).
We estimated the significance of improvement of fit by the first model over the second model using the chi-square test with one degree of freedom.
It is worth mentioning that, of course, we could vary the amount of re-weighting the variances of observations in the other models until the (chi ^2 approx 1).
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