  The recent interest in human dynamics has led researchers to investigate the
stochastic processes that explain human behaviour in different contexts. Here
we propose a generative model to capture the essential dynamics of survival
analysis, traditionally employed in clinical trials and reliability analysis in
engineering. In our model, the only implicit assumption made is that the longer
an actor has been in the system, the more likely it is to have failed. We
derive a power-law distribution for the process and provide preliminary
empirical evidence for the validity of the model from two well-known survival
analysis data sets.
