The results show that the proposed models fit significantly better than other existing NHPP models based on the studied criteria.
In the case of the Cas A XPS, we find our atmosphere models fit significantly better than blackbody models, although a wide range of radii is formally permitted.
In both cases, selection models fit significantly better the KLK2 and KLK3 data than neutral models (table 3), and eight (18, 67, 69, 109, 177, 205, 210, and 250) and five (45, 189, 203, 238, and 248) codon positions were identified as being positively selected in KLK2 and KLK3, respectively (table 3).
The results of RSM revealed that regression model fitted significantly at p≤0.01.
Although this model fitted significantly better than the original model according to the scaled χ2-difference test, comparative fit indexes were still clearly unacceptable.
The bifactor model fitted significantly better than the one-factor model (χ2 (10) = 358.08; p < 0.001).
The Mendelian model was accepted when (1) the general model did not show a significantly better fit to the data than the Mendelian model and (2) the general model fitted significantly better than the sporadic model.
Similar to the positive trials we found that although a linear growth curve model, excluding the Quadratic slope factor, described the data adequately (CFI = .99, SRMR = .03), the linear model fitted significantly worse than the non-linear model (χ(5) = 41.75, P < .001), and the non-linear model was therefore used in the analyses of the family data.
The results show that the proposed logistic fault-detection model fit significantly better than other existing NHPP models based on all three goodness-of-fit criteria.
