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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1974/5585
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| 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 Theses & Dissertations
Mathematics & Statistics Graduate Theses
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