Sentence examples for predictor criteria from inspiring English sources

In sum, WNV presence in both vector and secondary human host populations can best be explained using the same predictor criteria, suggesting a common ecological mechanism driving viral occurrence.

The first 15 clinical tests displayed are defined according to combinations of 4 influenza predictors ("criteria") present in a subject: acute onset, fever, cough, and body aches.

To establish a mediation effect, first the predictor-criterion correlation must be significant and meaningful.

Third, the mediator must be associated with the criterion measure, and finally, the predictor-criterion correlation must be attenuated when the mediator variable is entered into the mix [ 50, 51].

Since "need for information" was the only attribute that was marginally higher in the exploratory and confirmatory subsamples (by 7%) than in the overall study sample of 6318 patients, particular attention was paid to predictor-criterion configurations with low p-values with regard to informational desire.

If the predictor-criterion configurations (11121)×1 with P11121 × 1 = 0.040347 and (12221)×1 with P12221 × 1 = 0.018876 (Table 2, confirmatory sample) are therefore taken into account when interpreting the prediction types, the result is that the active role is preferred regardless of the informational desire of patients age 55 and younger with a high educational level.

Maximum predictability can only be obtained when predictor and criteria are symmetrical (see also Ackerman and Beier 2006).

Drop-out that was selective on both variables suppressed the regression coefficient (but less so than in the example in which drop-out was selective on the criterion only) and also reduced the correlation between predictor and criterion (r = 0.77 after drop-out).

Then, the mean of the observed correlations was computed and corrected for measurement unreliability in the criterion (i.e., job performance) and for restriction of range in predictor and criterion measures.

That means the Taylor-Russell tables are appropriate only if "the assumptions of bivariate normal, linear, homoscedastic relationships between predictor and criterion" [14, p. 197] are fulfilled.

For one, use of the Taylor-Russell tables assumes "bivariate normal, linear, homoscedastic relationships between predictor and criterion" [14, p. 197].