This paper reviews methods for the analysis of event history data by both parametric (exponential/Poisson) and semi-parametric methods. It identifies a need for software for handling the data structures of complex event histories and shows that, with such software, most Markov and semi-Markov models of event history data may be dealt with in the framework of generalized linear models. Finally, the emergent 'frailty' models for associated risks are discussed together with their implications for statistical software.