Cohort studies commonly involve a single determination of exposure, and one or more assessments of whether or not the outcome of interest has occurred. This approach is appropriate when the exposure does not change with time, and when one can readily determine the time of outcome (for example, mortality). If either of these conditions is not met, however, we may introduce bias into the estimate of effect, since we may misclassify individual members of the cohort with respect to exposure, outcome or both. We can reduce this bias by measuring exposure and outcome on more than one occasion. In this paper, we illustrate the design and analysis issues that arise in such circumstances, by reference to an ongoing prospective study of the relationship between genital papillomavirus infection and risk of cervical intraepithelial neoplasia. This study entails annual assessments of the status of the study subjects with respect to both conditions. In particular, we examine the implications that use of this design has on the statistical power of the study.