Which factor most directly influences a study's statistical power?

Which factor most directly influences a study's statistical power?

• A. Investigator's experience
• B. Publication venue
• C. Sample size
• D. Duration of the study

Answer: (C)

Power is the probability of detecting a true effect when one exists. It increases as a study gathers more information about the population. The most direct way to gain that information is by increasing the number of observations: a larger sample size reduces sampling error, makes the test statistic more likely to exceed the significance threshold if an effect is present, and thus raises power. Investigator experience and publication venue don’t change the mathematical likelihood of detecting a real effect—they influence study design or dissemination, not the core probability. Duration of the study could affect power only indirectly (for example, by limiting enrollments or altering measurements), but it does not directly set power the way sample size does. Therefore, the factor that most directly influences statistical power is the sample size.

Power is the probability of detecting a true effect when one exists. It increases as a study gathers more information about the population. The most direct way to gain that information is by increasing the number of observations: a larger sample size reduces sampling error, makes the test statistic more likely to exceed the significance threshold if an effect is present, and thus raises power.

Investigator experience and publication venue don’t change the mathematical likelihood of detecting a real effect—they influence study design or dissemination, not the core probability. Duration of the study could affect power only indirectly (for example, by limiting enrollments or altering measurements), but it does not directly set power the way sample size does. Therefore, the factor that most directly influences statistical power is the sample size.