Noncompliance is an important concern in randomized trials and must be taken into account when calculating sample sizes. The effect of noncompliance is usually assessed through a simple binary model that assumes that the patient either does or does not comply with the allocated treatment. In this article I present an example from cancer prevention, and show that different time courses of noncompliance can have different effects on the power, with widely varying estimates of the sample size required. The time course as well as the level of noncompliance should be considered when planning trials with long-term treatments.