statistical power

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sta·tis·ti·cal pow·er

in Neyman-Pearson hypothesis testing, the probability of rejecting the null hypothesis when it is false; the complement of an error of the second kind.
Farlex Partner Medical Dictionary © Farlex 2012
References in periodicals archive ?
Caption: FIGURE 1: Statistical power versus ICD code instances, baseline model.
Third, low statistical power and confounding effects combine to generate sizeable upward bias in detected price impacts and damages (i.e., overstating the magnitude of a price impact and damages).
In comparison, when [rho] [not equal to] 1, longitudinal studies always provide more statistical power than their cross-sectional counterparts.
Empirical statistical powers were estimated by testing genotypic difference from the unbalanced data simulated with 2 to 5 loci by the Bayesian method by Gibbs sampling.
Low statistical power contributes to an increased likelihood of making a Type II error (Onwuegbuzie, 2004), thereby causing important findings to be either misreported or not even published.
To increase the statistical power, if required, more sample size can be used or the level of error a can be increased (Foster, 2001).
Previous studies on the possible association between benzene exposure and lymphoma have been complicated by problems with exposure misclassification, outcome classification, and low statistical power. Vlaanderen et al.
"What makes our results so unique is that we had a very large sample size, and since we combined data across many studies, we had more statistical power to detect associations between cancer and coffee."
Via the extension, Algeta emphasized that the statistical power of the trial will be increased to 90%, thereby further raising the likelihood of proving the efficacy of the candidate drug.
Finally, power values were low for both confidence intervals and more studies are needed to improve statistical power.
This study summarizes and analyzes average statistical power and effect sizes in empirical entrepreneurship research.
As it happens, the effect size of interest is a mandatory variable in any a priori calculation of statistical power, along with the expected sample standard deviation (2-4).

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