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Prevalence data—models, likelihood, and binomial regression

This chapter examines prevalence data, using a dataset which contains the number of diabetes patients and the total number of persons in Denmark as of January 1, 2010, classified by age and sex. Prevalence of a disease condition in a population is merely the proportion of affected people. The chapter uses prevalence to illustrate core modelling concepts: the model itself, the likelihood, the maximum likelihood estimation principle, and the properties of the results, all of which underlies most modern epidemiological methods. It also explains the concept of a statistical model leading to the distinction between empirical and theoretical prevalences. The chapter then focuses on the task of comparing different models for the same data, models that describe data in various degrees of detail.