The aim of survival analysis is to study if and when some event occurs. With continuous-time analysis subjects are followed until the time they experience the event or drop out. In practice, subjects cannot always be followed continuously and event occurrence is measured in time periods. This type of survival analysis is known as discrete-time survival analysis and measuring subjects discretely rather than continuously results in a loss of information. The aim of this paper is to study the effects of discretizing survival times for randomized controlled trials by means of a simulation study. It is shown that parameter and standard error biases of both approaches are small and those of the discrete-time approach are only slightly larger than those of the continuous-time approach. The number of time periods has a negligible effect on bias. Power levels hardly differ across the two approaches, so following subjects continuously is not necessary, except when a detailed estimate of the underlying baseline hazard function is needed.