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So in fact the deviance test leads to a p-value that would indicate that the model is not true when n=10 and this is incorrect.
The deviance test (p ≤ 0.001) was applied for testing interactions.
According to the deviance test, the M2 model was superior to the M1 model.
The growth curve and deviance test were obtained from the multilevel analysis discussed below.
Possible outliers were identified using the Δβ and Δ deviance test [ 5].
Goodness of fit was evaluated using the Hosmer-Lemeshow test or a deviance test comparing saturated and reduced models.
Similar(41)
For low-dimensional problems, classical deviance tests are also included and compared with penalized likelihood approaches.
Main effects and interactions were also tested using likelihood ratio (deviance) tests.
We tested the influence of the explanatory variables by means of deviance tests.
Deviance tests or likelihood ratio tests were used to compare the relative fit of the different models.
Statistical interaction was assessed on the multiplicative scale by deviance tests based on comparisons of likelihoods in nested models with and without cross-product terms.
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