The nested case-control design is frequently used to evaluate exposures and health outcomes within the confines of a cohort study. When incidence-density sampling is used to identify controls, the resulting data can be analyzed using conditional logistic regression (equivalent to stratified Cox proportional hazards regression). In these studies, exposure lagging is often used to account for disease latency. In light of recent criticism of incidence-density sampling, we used simulated occupational cohorts to evaluate age-based incidence-density sampling for lagged exposures in the presence of birth-cohort effects and associations among time-related variables. Effect estimates were unbiased when adjusted for birth cohort; however, unadjusted effect estimates were biased, particularly when age at hire and year of hire were correlated. When the analysis included an adjustment for birth cohort, the inclusion of lagged-out cases and controls (assigned a lagged exposure of zero) did not introduce bias.