'Power' is the probability that a test will reject an untrue null hypothesis. In health economics, 'power' most frequently refers to the statistical power of a clinical trial. In general, a trial ought to be big enough to have a high chance of detecting a statistically significant effect and one that is also clinically or biologically significant - if one exists. Sample size is therefore critically important. The researcher needs to decide the degree of difference between two groups being compared that would constitute a minimally clinically significant effect. How large the sample needs to be to deliver statistically significant results can be determined by using a statistical nomogram. The power of the study (moderate, high or very high) is the chance of detecting a prespecified true clinically relevant difference between the groups at a prespecifiedp-value (usually p < 0.05).
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