Sentence examples for difference in the deviance from inspiring English sources

The model comparisons between the linear and the threshold models, based on both the AIC and the difference in the deviance, always chose the linear exposure response model.

To assess whether one model had a better fit over another, the difference in the deviance statistic was used (Table  3).

Specifically, we assessed the level of extra binomial variability or overdispersion in our model due to trust and year by examining the difference in the deviance for the full model and the model with trust year omitted.

If no substantial difference can be detected between the two model fits (ie, if the difference in the deviance information criterion for the two models would not exceed three points), heterogeneity may be low.

A new criterion, TE-optimality, is defined, based on the difference in the deviances from the two models, and comparisons are made with T-, Ds- and D-optimality.

The differences in the deviance between the linear and spline models did not indicate a significant improvement in the fit of the spline versus linear models.

We have extended this approach to enable the use of individual subject data in the large sample size situation, using the asymptotic distribution of differences in the deviance as the basis for estimation of overdispersion.

We began the model selection process by evaluating the predictive performance of each model and the variable combinations through cross-validation, for which the data were split into training and test sets, and the differences in the deviance and an R 2 measure based on the Brier score Brier score (iRBS) were calculated (described in the Additional file 1).

For model comparisons, we evaluated the differences in model deviance and the related P values from goodness of fit tests at a 5% significance level using the difference in the observed deviance and the degrees of freedom between a set of nested models.

Again, the faceted model with four correlated dimensions outperformed the single-factor approach, as the difference in the final deviances was statistically significant (Δ dev = 595.17, Δdf = 9, p < 0.001).

Linearity was assumed if the p-gain defined as the difference in normalized deviance between the GAM model and the linear model for the same exposure and outcome (Royston and Ambler 1998) was > 0.10.