Sentence examples for test of omission from inspiring English sources

Only those niche models possessing both a p value less than 0.05 for the binomial test of omission and an AUC greater than 0.75 were used in this analysis.

The accuracy of each model was then determined by performing both a threshold-dependent binomial test of omission and a threshold-independent receiver operating characteristic analysis with those cells set aside during model development [11].

In the threshold-dependent binomial test of omission a threshold of 0.10 was used to classify each vector as either present or absent in each cell, with a vector present in a given cell if the niche model assigned it a value greater than 0.10 in that cell and absent otherwise.

Maxent simulations are analyzed using binomial tests of omission rates and the area under the receiver operating characteristics (ROC) curves to examine the model performance, the accuracy of geographic distributions, and the significance of environmental variables for discriminating suitable habitats.

Correspondingly, if we train larvae differentially, that is, reward one of the odors but not the other and omit one of the odors during test, the omission of the less-learnable odor 1OCT is of negligible effect (as compared with the scores found when both trained odors indeed are present at test: Figure 2C; MWU-test: U = 210.0; P > 0.05/2; N = 23, 21).

Many of the Dyen list cognates are marked uncertain, so Dr. Gray was able to test whether omission of the doubtful cognates made any difference (it did not).

§P value for likelihood ratio test from omission of interarm differences from multivariable model 2. *Adjusted for Framingham 10 year cardiovascular risk score.

Data from a related task requiring uncertainty monitoring (a scholastic aptitude test where omission of responses was allowed), revealed an analogous reduction in test score when the penalty for incorrect answers was increased (Higham, 2007).

†P value for likelihood ratio test from omission of interarm differences from multivariable model 1. ‡Adjusted as for model 1 plus mean blood pressure, presence of diabetes, and pre-existing vascular disease.

†P value for likelihood ratio test from omission of interarm differences from multivariable model 1. ‡Adjusted as for model 1 plus mean blood pressure, presence of diabetes, and pre-existing vascular disease (for all cases analyses).

§P value for likelihood ratio test from omission of interarm differences from multivariable model 2. At recruitment 183 participants had no pre-existing cardiovascular disease; 28% (n=51) had an interarm difference in systolic blood pressure of 10 mm Hg or more and 11% (n=20) a difference of 15 mm Hg or more, and 6% (n=11) had an interarm difference in diastolic blood pressure of 10 mm Hg or more.