Sentence examples for model then retains from inspiring English sources

The updated forecasting model then retains its accuracy for later turbidity forecasts.

For all outcomes, sociodemographic variables with a P-value<0.2 in the bivariate analyses were entered into the multivariate model, then retained in the final model if P<0.05.

We fitted full models initially then retained variables if these had a HR of <0.80 or >1.20 (for binary variables) and were statistically significant at the 0.05 level.

32 We fitted full models initially and then retained variables if they had a hazard ratio below 0.80 or above 1.20 (for binary variables) and were statistically significant at the 0.05 level.

The badger-related, sett-related and herd-related variables which demonstrated the most significant univariable associations with time to first confirmed bTB herd breakdown were then retained for multivariable model building controlling for local farm-level risks [Supplementary Information S1].

Variables associated with ADL impairment with a p-value of <0.05 were then retained for future models and the proportion of the variance of ADL impairment explained by the variable was assessed by the value of the R statistic.

Specifically, in GARP, we retained only the 20% of models that showed lowest omission errors, and then retained only the central 50% of the frequency distribution of proportional area predicted present (an index of commission error); the result was 10 'best subsets' models (binary raster data layers) that were summed to produce a best ensemble estimate of geographic projection.

We then retained only the CKE models for which the optimized fit to microarray data is of high quality and validated multiple miRNA-mRNA pairs.

Another possibility is to fit models over a grid of values of ω and then retain the value that maximizes predictive performance.

The variables that passed the criteria for effect measure modification and confounding were then retained and fitted into the logistic regression model.

In this paper, we introduce a new method for backbone extraction that does not rely on any particular null model, but instead uses the empirical distribution of similarity weight to determine and then retain statistically significant edges.