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Please use this identifier to cite or link to this item: http://hdl.handle.net/1974/5585

Title: A new approach in survival analysis with longitudinal covariates
Authors: Pavlov, Andrey

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Keywords: survival analysis
longitudinal covariates
joint model
state space model
hidden Markov model
Kalman filter
event history chart
conditional expected remaining lifespan
Issue Date: 2010
Series/Report no.: Canadian theses
Abstract: In this study we look at the problem of analysing survival data in the presence of longitudinally collected covariates. New methodology for analysing such data has been developed through the use of hidden Markov modeling. Special attention has been given to the case of large information volume, where a preliminary data reduction is necessary. Novel graphical diagnostics have been proposed to assess goodness of fit and significance of covariates. The methodology developed has been applied to the data collected on behaviors of Mexican fruit flies, which were monitored throughout their lives. It has been found that certain patterns in eating behavior may serve as an aging marker. In particular it has been established that the frequency of eating is positively correlated with survival times.
Description: Thesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2010-04-26 18:34:01.131
URI: http://hdl.handle.net/1974/5585
Appears in Collections:Queen's Graduate Theses and Dissertations
Department of Mathematics and Statistics Graduate Theses

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