Which of the following is associated with increased power in a study?

• A Decreasing the sample size
• B Reducing the effect size
• C Increasing measurement error
• D Increasing the significance level from 0.01 to 0.05 ✓

Explanation

Power is the probability of correctly rejecting a false null hypothesis. Increasing the significance level from 0.01 to 0.05 makes it easier to reject the null hypothesis, thereby increasing power, though it also raises Type I error risk. Decreasing sample size, reducing effect size, and increasing measurement error all decrease power by making it harder to detect a true difference.

Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.

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