Smoothing geographical data, particularly rates of disease.

This paper proposes a linear smoother for geographically-defined data that consist of standardized rates (for example, adjusted for age). The smoother is viewed as a special case of one that applies to data in the form of ratios, and situations are described under which such a smoother can and cannot be useful. Its application to mortality rates due to prostate cancer in both whites and non-whites demonstrates its potential to highlight features in the data that might otherwise remain obscure. Some open questions concerning inference of apparent trends are discussed.