Examples of using Statistical power in English and their translations into Spanish
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a meta-analysis has greater statistical power than the clinical trials it includes.
the Life Span Study, but do not yet have the statistical power to add much to the quantitative estimates of risk.
this failure to address assignment bias means that the statistical power is weak.
The true power of STR analysis is in its statistical power of discrimination.
Increasing sample size is often the easiest way to boost the statistical power of a test.
a non-parametric alternative to the t-test can often have better statistical power.
with an appropriate control group and sufficient statistical power to verify the results.
Despite the statistical power and results that are easy to generalize,
The sensitivity of a design is measured by statistical power, which, among other factors, depends on the sample size- that is,
the research maintained sufficient statistical power.
The Committee's analysis includes an assessment of statistical power, the potential for systematic error
the current absence of radiation-specific biomarkers for health effects and the insufficient statistical power of epidemiological studies.
the definition based on the median is recommended as the choice that provides good robustness against many types of non-normal data while retaining good statistical power.
there will always be a positive value greater than zero that has more statistical power than zero.
reducing the statistical power of the experiment, making it impossible for the experiment to identify important
This information was used in a statistical power analysis to estimate the sample sizes of hauls needed to detect different proportional differences in densities between two areas using a two-sided 5% test with power 0.8.
type II error of 5% i.e. 95% confidence and 95% statistical power.
which do not have any statistical power, the value of the relative risk found for any supposedly"statistically significant" results is likely to be a substantial overestimate of the"true" risk.
Jacob Cohen, a New York University professor of psychology, analyzed quantitative methods involving statistical power and effect size,
Noting that ad hoc TASO requested that all working groups consider required statistical power and importance of coverage levels(SC-CAMLR-XXVII/BG/6, paragraph 3.27), the Working Group recalled that it had considered statistical power previously(e.g. WG-FSA-05/50) which led to