Multiple regression in geographical mortality studies, with allowance for spatially correlated errors.

In order to provide clues to the aetiology of a disease, mortality indices for different areas are often related to explanatory variables by using multiple regression. However, mortality in nearby areas may be similar for reasons not attributable to the covariates, so the errors will not be independent. This paper suggests a way of finding a parameterized form for the correlated error structure by examining the residuals from an ordinary least squares regression. Such a model is then fitted by using maximum likelihood. An example based on cardiovascular mortality in British towns is used to illustrate the problem and our solution.