Sentence examples for deviance was explained by from inspiring English sources

All three variables were highly significant (Anova: P < 0.001), but differed in influence; 18.5% of the total deviance was independently explained by family, while 0.5%and0.4%4% of the deviance was explained by exposure time and gender, respectively.

Explanatory power went up even further using only US cases: 75% of deviance was explained with changes in population density, temperature, and precipitation.

Walden and colleagues [ 4] found that the relationship between peer deviance and alcohol use was explained by common environmental factors (although they were not examining peer alcohol use per se).

The study used a measure of peer deviance and found that the association with alcohol use was explained by common environmental influences (i.e. environmental influences that make the twins more similar), with no evidence for genetic influences.

This model explained 11.7% of the deviance, indicating most of the variability in diet could not be explained by the predictors.

We also calculated a deviance-based R-squared measure that may be interpreted as the proportion of uncertainty in the relevant outcome that has been explained by the model.

For LNHL, most of the deviance reduction of the simultaneous analysis can be explained either by the variable employed on the date of conception or by the variable employed in the year of diagnosis.

Variability in coverage was primarily explained by population factors, with general practice characteristics only accounting for a small fraction of the residual variability (<2% of total deviance after adjustment for population factors).

The trait with the most explained deviance was occipital-nasal length, a hybrid measure of nasal length as well as width [Fig. 1].

In LMs, R is defined from the residual sum of squares, and in GLMs the goodness of fit is evaluated in terms of the deviance: the percentage of deviance explained by the model.

Finally, although significance thresholds in maSigPro-GLM maintain their statistical meaning, the goodness of fit, which is used in the second step of maSigPro to select genes with well-fitted models, is evaluated in GLMs in terms of the deviance: the percentage of deviance explained by the model.