The aim of this project is the development and evaluation of statistical methods based on intensity function models for the analysis of data from studies where an individual study subject may experience multiple point events over time. For example, an individual animal may have multiple distinct tumor occurrences following exposure to a carcinogen. For such studies, in addition to the occurrence times of point events, there may be covariate information pertaining to each subject (e.g. type of drug therapy). Often it is the relationship between the point process of event times and the covariates that is of primary interest. The methods under development offer a comprehensive means of examining the relationship between the point process and the accompanying covariates. The main focus of this project is the evaluation and application of a general class of regression-type models for the intensity function of the point process. The intensity is represented as the product of a history-dependent, stratum-specific baseline intensity with history-dependent time argument and a regression expression is selected covariates. A likelihood expression for this model class has been developed. Under this proposal, parameter estimation and computational procedures based on this likelihood expression will be examined in order to evaluate their tractability and practicability.