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Standard categorical analysis is based on an unrealistic model for dose-response and trends and does not make efficient use of within-category information. This paper describes two classes of simple alternatives that can be implemented with any regression software: fractional polynomial regression and spline regression. These methods are illustrated in a problem of estimating historical trends in human immunodeficiency virus incidence. Fractional polynomial and spline regression are especially valuable when important nonlinearities are anticipated and software for more general nonparametric regression approaches is not available.