Abstract
This paper reviews the analysis of prospective epidemiological studies using general linear models to describe disease Incidence, It is shown that, apart from problems arising from the large size of most studies of this type, these models may be fitted by maximum likelihood (using GLIM, for example) assuming a Poisson likelihood.Alternative methods for dealing with large-scale data are discussed, and some simple procedures for dealing with common problems are outlined.The relationship of the approach to multiple logistic analyses is indicated.