(33pp.) We present a novel approach to the empirical Bayes analysis of aggregated survival data from different groups of subjects. The method is based on a contingency table representation of the data and employs transformations to permit the use of normal priors. In contrast to the case of a single survival curve, the empirical Bayes analysis of families of such curves leads to estimates which offer a qualitative improvement over classical estimates based on the ratio of occurrence to exposure rates. This method is illustrated with data on the attainment of the doctoral degree from three major universities.