Review Question - QID 103885

Statistical power refers to the ability of a study to correctly identify a true association.

The results of a clinical study can either be discordant or concordant with reality. If an association between an exposure and an outcome is true, then the study can either erroneously not find that difference (Type II error) or it can correctly identify it (true positive). The power of a study refers to its ability to yield that true positive.

Rosner provides the definition of power as how likely it is that a statistically significant difference will be detected based on a finite sample size if the alternative hypothesis is true--that is, if the null hypothesis is false.

Drummond et al. describe how the power is affected by the sample size of the study. If a sample size is too small, the study will have insufficient power to detect differences between groups, if differences do exist.

Illustration A depicts all possible outcomes when performing a clinical study.

Incorrect Answers:
Answer 1: Type I error (alpha) is the probability detecting an association when no association exists.
Answer 3: Type II error (beta) is the probability of not detecting an association when an association does exist.
Answer 4: The true negative rate is the probability of not detecting an association when no association exists.
Answer 5: The first derivative of work is the physical definition of power, not the statistical. Your premedical studies will not help you here.