Sentence examples for model and contrast from inspiring English sources
The connectedness of the designs is justified from two perspectives: linear model and contrast estimability.
Multi-objective model and contrast between multiple objectives, application of imprecise (cardinal and ordinal) data in model, more discrimination power compared to the classical DEA.
As cowhage has not been employed in previous clinical or translational studies, we aimed to test the validity of cowhage as an experimental itch model, and contrast it with histamine, in AD patients and healthy controls.
Finally, we describe the utility of the GCA model and contrast its predictions with those of the TEF approach.
The parameter estimates were calculated for all brain voxels using the general linear model, and contrast images comparing each condition against fixation (i.e., the baseline) were computed [Friston et al., 1995b].
Therefore, we first modeled the effects of luminance (luminance-only model) and contrast (contrast-only model) separately, before assessing their unique effects in a model including them both (LumCon model).
Therefore, data obtained from the RPE REP-1 siRNA model and contrasted with that obtained from the study of peripheral cells of the CHM patients reveal valuable and novel information with respect to understanding the mechanism and development of the CHM disease in the human population.
The effectiveness of social distancing interventions was determined using the PNG model and contrasted with the Australian model.
In terms of selection tests, we used a stringent branch-site codon model, and contrasted duplication branches with speciation branches.
To test for interactions, we added the interactions one at a time to the main effects model and contrasted the likelihoods of the models including and excluding the interaction term using the Log-likelihood ratio test.
We also calculated the proportion of correct predictions provided by the final model and contrasted the result with the proportion of correct predictions from an uninformative model where no explanatory variables were fitted.
