A New Approach in Survival Analysis with Longitudinal Covariates
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Authors
Pavlov, Andrey
Date
2010-04-27T21:36:33Z
Type
thesis
Language
eng
Keyword
Survival Analysis , Longitudinal Covariates , Joint Model , State Space Model , Hidden Markov Model , Kalman Filter , Event History Chart , Conditional Expected Remaining Lifespan
Alternative Title
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
Citation
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This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.