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Abstract
In this article, the second of a series on the analysis of time to event data, we address the case in which multiple predictors (covariates) that may influence the time to events are taken into account. The hazard function is introduced, and is given in a form useful for assessing the impact of multiple covariates on time to an event. Methods for the assessment of model fitting are also discussed and an example with cancer survival as outcome with the presence or absence of multiple genes as covariates is presented.