Sentence examples for prevalence accuracy from inspiring English sources

To test this possibility, we correlated each significant predictor of low prevalence accuracy with false alarms.

The overall accuracy regression model predicted low prevalence accuracy, F 5, 135) = 31.68, p < 0.001, adjusted R 2 = 0.523.

The multiple regression model significantly predicted low prevalence accuracy, F 4, 136) = 36.29, p < 0.001, adjusted R 2 = 0.502.

We then used our cognitive measures as predictors in a multiple regression model to predict low prevalence accuracy.

Table 2 Low prevalence accuracy regression results   t p value β High prevalence performance 9.99 <0.001 0.60 K 2.27 0.03 0.14 Vigilance 2.05 0.04 0.13 Attentional control 2.59 0.03 0.14 Extraversion –2.63 0.009 –0.15 t, p, and β values for each predictor in the final regression model for low prevalence accuracy.

Given the strong association between high and low target prevalence accuracy, using one's performance on a high prevalence search task as a proxy for their likely ability to detect low prevalence targets may be a much more economical approach.

It is worth noting that the most powerful predictor of low prevalence search accuracy was high prevalence search performance.

Ultimately, our goal is to assemble a battery of tasks that can be used to reliably predict low prevalence search accuracy.

1. Gaynes BN, Gavin N, Meltzer-Brody S, Lohr KN, Swinson T, Gartlehner G, Brody S, Mille WC et al: Perinatal depression: prevalence, screening accuracy, and screening outcomes.

However, in longitudinal incidence and prevalence studies, accuracy in measurement overall and over time is essential.

The prevalence and accuracy of CCA was calculated as the percentage of the total number of subjects.