Sentence examples for marginal factors from inspiring English sources

The marginal factors in the past four or six weeks have looked slightly better for Mr. Romney than Mr. Obama.

Elevation zone, minimum distance to grassland, and species were marginal factors of the occurrence of debarking of saplings and trees and sapling density (Table 4).

Since levels of haemoglobin and testosterone were significant or marginal factors for OS, we classified patients into three groups: (patients presenting two risk factors (anaemia and Low TL), one risk factor, or without risk factors), and a Kaplan Meier model was used to analyse the OS.

Until then, Morales had been a marginal factor in Bolivian politics; afterward, running as "America's worst nightmare," he received 20.9 per cent of the vote.

In Haryana and Bihar, Congress remained a marginal factor -- and may have little choice but to join forces with Mr. Yadav in Bihar, despite Congress's harsh criticism of him, to stop its Hindu nationalist rival from coming to power there.

For instance, since rbST is prohibited for USDA certified organic dairies and the marginal value product of its use would unlikely exceed the marginal factor cost for pasture-based production, expected signs for these systems would be negative for rbST.

It is their task to cure the dysfunctional political system, in which popular opinion is a marginal factor.

Based on the multi-pollutant analysis among the 25 HAPs, when computing the marginal Bayes factors from the SSVS posterior, we identified two with a Bayes factor greater than or 1 (Table  4): quinoline (ORhigh = 2.06, 95% CI: 1.11-3.87, Bayes factor = 1.01); and trichloroethylene (ORmedium = 2.00, 95% CI: 1.14-3.61, Bayes factor = 3.79).

Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen.

The presence of PIK3CA kinase domain mutations and helical domain mutations were marginal prognostic factors of both RFS (P = 0.067 and P = 0.052) and BCSS (P = 0.10 and 0.077), respectively (Fig. 2).

Predictive models using machine learning algorithms may therefore facilitate recognition of clinically important risk and variables in patients with several marginal risk factors that may otherwise not be identified.