Statistical Methods for the Analysis of Recurrent Events and Event History Data

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Statistical methods based on the occurrence of a single event are not adequate for a comprehensive understanding of data producing mechanisms of event processes with complex event histories. Therefore, statistical methods and models designed for the analysis of recurrent events and other complex event histories are needed in many fields of study. Models that ignore the past of an event process are incapable of comprehensive understanding of the underlying process. Dynamic models are intensity-based stochastic process models which are used to examine the effect of past event occurrences on the present or future evolution of a process. Dynamic models include dynamic covariates, which are essentially internal time-dependent explanatory variables. The inherent nature of dynamic covariates and their complex relations with interventions, treatment effects and heterogeneity make modelling and inference challenging issues when dynamic covariates are present. Another important issue is the use of the outcome-dependent study designs in event history settings. Such designs provide a cost-effective way to analyze event history data. However, there are many methodological problems in event history settings. The overarching goal of this research program is to address important issues in the statistical analysis of recurrent events and event history data, motivated by the need for complex models and related methods of analysis in engineering and scientific settings. Therefore, I will explore dynamic models and outcome-dependent study designs for recurrent events and event history, and develop novel statistical methods in various settings. Emerging methodological and challenging issues that arise in epidemiology, medicine and reliability engineering motivate this research program. Research carried out through this program will have direct impact on important application areas in Canada. For example, the developed novel models will be instrumental in understanding the recurrent event occurrences in health services in Canada, providing concrete evidence to decision-makers in health policy to improve care activities and hospital utilization, and to reduce the total hospitalization cost. The anticipated outcomes of the research will also be beneficial for power generation companies in Canada to improve their reliability programs and to determine their maintenance policies, which minimize the total cost of operation and maximize the availability of repairable systems.