In occupational settings, carcinogenic exposures are often repeated or protracted over time. The time pattern of exposure accrual may influence subsequent temporal patterns of cancer risk. The authors present several simple models that may be used to evaluate the influence of time since exposure or age at exposure on cancer incidence or mortality in an occupational cohort. A cohort of 40,415 nuclear industry workers was identified via the Canadian National Dose Registry. Vital status and cause of death were ascertained through 1994. Associations between ionising radiation and mortality due to lung cancer, leukaemia, and cancers other than lung and leukaemia were quantified using conditional logistic regression models with risk sets constructed by incidence density sampling. A step function, a bilinear function, and a sigmoid function were used to evaluate temporal variation in exposure effects. Step and sigmoid functions were used to explore latency and morbidity periods. For analyses of lung cancer, leukaemia, and other cancers the best fitting models were obtained when exposure assignment was lagged by 13, 0, and 5 years, respectively. A bilinear function was used to evaluate whether exposure effects diminished with time since exposure. In analyses of lung cancer and leukaemia, there was evidence that radiation effects attenuated with protracted time since exposure. In analyses of age at exposure, there was evidence of variation in radiation mortality associations for analyses of lung cancer and leukaemia; discounting radiation doses accrued at younger ages (for example, 15-35 years) led to significant improvements in model fit. This paper illustrates empirical approaches to evaluating temporal variation in the effect of a protracted exposure on disease risk.