Exponential family models and statistical genetics

This article describes the evolution of applied exponential family models, starting at 1972, the year of publication of the seminal papers on generali zed linear models and on Cox regression, and leading to multivariate (i) ma rginal models and inference based on estimating equations and (ii) random e ffects models and Bayesian simulation-based posterior inference. By referri ng to recent work in generic epidemiology, on semiparametric methods for li nkage analysis and on transmission/disequilibrium tests for haplotype trans mission this paper illustrates the potential for the recent advances in app lied probability and statistics to contribute to new and unified tools for statistical genetics. Finally, it is emphasized that there is a need for we ll-defined postgraduate education paths in medical statistics in the year 2 000 and thereafter.