Sentence examples for models under comparison from inspiring English sources

(C ) ROC curves for the three predictive models under comparison, i.e., the p53 mutation status, the 215-feature and the 13-gene signature models.

The relative likelihood can be used to calculate the Akaike weights (w i ): (12) w i = exp (- 0. 5 · Δ i ) ∑ r = 1 R exp (- 0. 5 · Δ r ), where R is the number of models under comparison.

I also urge caution when using dpp-msBayes due to the lack of theoretical validation of Bayesian model choice when the full data are replaced by summary statistics that are insufficient for discriminating across models under comparison [ 44], which is certainly the case here.

In short, the DeLong method is designed to test the null hypothesis that the true performance of two fixed models are equal: A r (1 ) = A r ′ (2 ), where the superscripts 1, 2 denote two models under comparison, and the subscripts indicate that the training data sets may be different.

Twice the difference in log likelihood (G = 2ΔLL) between the two models under comparison is significant at level α if G = 2ΔLL > χdf, α with the degrees of freedom equal to the difference in the number of parameters between the two models [ 48, 49].

The method of Mantel-Haenszel was used to calculate the odds ratio for the pooled data in a fixed-effects model, and, if there was evidence for heterogeneity, the DerSimonian-Laird method was used for the pooled odds ratio in a random-effects model, under pairwise comparisons of the different genotypes and dominant, recessive, and additive inheritance models.

We further calculated the likelihood under comparison between models M3r and M2r to explore the assumption of the same selective constraints at two TFIIAγ genes after the duplication event.

The results described under Model Comparison above show that a typical post-decision wagering measure – Type II hit rate – is subject to a bias that can be explained by loss aversion, despite the underlying Type I sensitivity to the stimulus remaining constant.

When the studies were stratified by the source of controls, a significant association was observed for population-based controls under the homozygote model, the dominant comparison model and the allelic model.

The shapes of the funnel plots appeared to be symmetrical, and the Egger test further suggested that there was no significant evidence of publication bias under some genetic models (allele comparison: P = 0.83; homozygote model: P = 0.39; dominant model: P = 0.29; recessive model: P = 0.23), but the heterozygote model showed significant publication bias (P = 0.02).

The critical part is in having explicit stochastic models (likelihood functions) for each of the hypotheses under comparison.