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dc.contributor.authorClement, Daviden_US
dc.identifier.otherbibid: 8213809
dc.description.abstractThis thesis analyzes censored data in recurrent event, longitudinal, and survival settings. In Chapter 2, a straightforward, flexible methodology is proposed to estimate parameters indexing the conditional means and variances of the interevent times in a recurrent event process. In Chapter 3, we analyze discretely and informatively observed multivariate continuous longitudinal data; missingness and terminal events are introduced in Chapter 4. In Chapters 3 and 4, the inter-event times are considered a nuisance and the goal is to estimate parameters driving the longitudinal process. To do this, we propose an innovative conditional estimating equation that can model individual trajectories. Finally, Chapter 5 uses these subject-specific trajectories to estimate parameters indexing the terminal event process and predict future survival for arbitrary subjects.en_US
dc.titleEstimating Equation Methods For Longitudinal And Survival Dataen_US
dc.typedissertation or thesisen_US Universityen_US of Philosophy D., Statistics
dc.contributor.chairStrawderman, Robert Leeen_US
dc.contributor.committeeMemberHooker, Giles J.en_US
dc.contributor.committeeMemberWells, Martin Timothyen_US

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