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The rejection of the null models is significant for the five LR tests.
It is also clear that the overall fits of the three models is significant because the Prob > F values of the model terms for the three responses are less than 0.05.
Unlike for Tp1 locus, the comparison between nested models is significant in cattle, Finally, the average ω is high in both cattle (0.78<ω<1.29) and buffalo (0.57<ω<0.68), as determined by the three most likely evolution models (Table 3).
If none of the nonlinear terms in either the second or third order polynomial models is significant, then linearity is assumed.
The Pearson correlation for both models is significant but weak with the LINfs3 model showing a slightly higher correlation (0.41, p=0.0001) than the LINiter model (0.34, p=0.0022).
To evaluate whether an improvement in prediction accuracy between the different prediction models is significant we compared the log10 pVL reduction at Week 8 for the patient samples classified to be in the at risk of X4 emergence group.
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All models are significant at α = 0.05.
In this case, none of the personality models were significant.
In the current study, four quadratic models are significant model terms (Table 4).
The lack of fit values for all models was not significant, showing that the fitted models are significant.
The Prob > F values are all less than 0.0001 which herald the models are significant.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com