Sentence examples for predictor power of from inspiring English sources

17 In our study, we defined a landmark time of 48 h; thus, we missed the earliest occurrence of coronary events and the associated predictor power of troponin.

But for most of its life, the group and producer recorded and mixed in mono, an earlier predictor of the power of 140 characters.

This would likely explain why absolute item difficulty was a significant predictor of power even after controlling for CAT item usage.

Two complementary statistical approaches, boosted regression trees and hierarchical partitioning, were used to model the responses of four fish species to 11 environmental predictors, and to quantify the independent explanatory power of each predictor.

The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples.

However, as we are interested in the relative importance of the two predictor variables, the explanatory power of the model as a whole is not a concern.

Please be aware however that both, recombination and expression measures will be noisy and as Plotkin and Fraser [ 40] highlight, one should not compare the explanatory power of predictors with standard regression techniques when the predictors contain different amounts of measurement noise.

Minor allele frequency is the strongest predictor, and heavily modulates the predictive power of all other predictors (results not shown; this is an expected consequence of sample size constraints/ascertainment bias within the individual source studies).

This finding exemplifies an instance when collinearity with a stronger predictor (eg, wave 1 SRO) overwhelmed the explanatory power of other predictors with weaker relationships.

The combination of the RILs' metabolic markers and the biomass variable as predictors yields a predictive power of 0.51 and 0.47 for C24- and for Col-heterosis respectively.

Combining geographic distance and environmental variation as predictors increased the explanatory power of the model to 48% (Table  3).