Ordered polytomous logistic regression is a useful technique for relating a dependent ordered categorical variable to both categorical and continuous independent variables. This paper demonstrates the practical implementation of this model to a large data set. The problem of selecting an appropriate subset of independent variables is considered. A method of checking the model's goodness of fit is described. Three methods of allocating subjects to categories are compared, one based on fixed proportions allocated to each category being most informative. A statistical policy for amalgamating adjacent categories is developed. These techniques are demonstrated by a study of the relationship of alcohol consumption to serum biochemistry and haematology in 7735 middle‐aged men. The ordered polytomous model is used here to estimate a summary measure of an individual's biochemical response to alcohol intake.