There are often several data sets that may be used in developing a quantitative risk estimate for a carcinogen. These estimates are usually based, however, on the dose-response data for tumor incidences from a single sex/strain/species of animal. When appropriate, the use of more data should result in a higher level of confidence in the risk estimate. The decision to use more than one data set (e.g., representing different animal sexes, strains, species, or tumor sites) can be made following biological and statistical analyses of the compatibility of the these data sets. Biological analysis involves consideration of factors such as the relevance of the animal models, study design and execution, dose selection and route of administration, the mechanism of action of the agent, its pharmacokinetics, any species- and/or sex-specific effects, and tumor site specificity. If the biological analysis does not prohibit combining data sets, statistical compatibility of the data sets is then investigated. A generalized likelihood ratio test is proposed for determining the compatibility of different data sets with respect to a common dose-response model, such as the linearized multistage model. The biological and statistical factors influencing the decision to combine data sets are described, followed by a case study of bromodichloromethane.