Sentence examples for model deviance to from inspiring English sources

Fit was evaluated using the ratio of model deviance to degrees of freedom, which should be close to one for a well-fitted model.

The ratio of the model deviance to the degrees of freedom was small (0.29) indicating that the model was a good fit.

The ratio of the model deviance to the degrees of freedom was small (0.17) indicating that the model fitted the data well.

The regression analyses produced similar results in the MB external validation data; the ratio of model deviance to degrees of freedom was close to 1.0 for the main effects model.

For NL, the main effects model provided a good fit to the data, as judged by the ratio of model deviance to degrees of freedom (ratio=1.0) and the AIC was smaller for a main effects model than for one with main and two-way interaction effects (3833.1 vs 3830.4); likelihood ratio tests revealed statistically significant main effects for sex (p<0.0001) and years since specialty (p=0.0006).

Results show that model 4, the four-dimensional model (see Table 1), is superior: it has lowest AIC, AICc, and BIC values, and the likelihood-ratio tests show statistically significant improvements in model deviance compared to both of the 2-dimensional models.

Results show that model 4, the eight-dimensional model (see Table 1), is superior: it has lowest AIC, AICc, and BIC values; and likelihood-ratio tests show statistically significant improvements in model deviance compared to both of the 2-dimensional models.

In the regression models, only potential confounders that led to a significant (p < 0.05) change in the model deviance or led to > 5% change in the log odds ratio (OR), in at least one of the three study regions, were included in the final models (Greenland and Rothman 1998a).

Model deviance was used to compare goodness of fit between (nested) models.

Lags were evaluated by separately fitting the single variable models for bronchiolitis and ILI for the 5 lags from -2 and +2 weeks to determine which had the best model fit according to model deviance and the strength of the parameter estimate.

to minimise transient model Deviance; where italicised φm minimises Dev subject to ERR ≥ 0, equivalent to σ ≥ 0. c At φm, σ and τ are the fitted Maximum Likelihood Estimate parameter values.