In the context of trial design, what is the impact of participant non-compliance or dropout on study power?

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When planning a trial, statistical power is the probability of detecting a true treatment effect if one exists, and it depends on sample size, variability, the true effect size, and the significance level chosen. If participants don’t follow their assigned treatment or drop out, you lose data from those individuals. That reduces the actual number of participants contributing usable information, which raises the standard error of the estimated effect and lowers the study’s power to detect a real difference. To keep the desired power, researchers often increase the initial sample size to account for expected attrition, or use design and analysis approaches (like intention-to-treat) to preserve information and minimize bias.

So the correct choice reflects that non-compliance or dropout can reduce achieved power and may require a larger sample size. Non-compliance or dropout does have consequences for outcomes, it doesn’t typically increase the observed effect size, and it doesn’t negate the need for randomization.