Estimation of the Base Hazard Function by Bootstrapping
This thesis examines the techniques in estimating the base hazard function by bootstrapping. The base hazard function is a crucial part of survival analysis. It is used to construct an estimate of the proportional hazard model for every individual. As in many methods for analysing survival data,...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2004
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| Online Access: | http://psasir.upm.edu.my/id/eprint/30/1/1000548962_t_FS_2004_2.pdf http://psasir.upm.edu.my/id/eprint/30/ |
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| Summary: | This thesis examines the techniques in estimating the base hazard function by
bootstrapping. The base hazard function is a crucial part of survival analysis. It is used
to construct an estimate of the proportional hazard model for every individual.
As in many methods for analysing survival data, this thesis utilizes the nonparametric
model of Kaplan Meier, the Cox proportional hazard regression of the parametric
model and the data validation by bootstrapping.
The Cox proportional hazard regression is used to model failure time data in censored
data. Bootstrapping schemes validate the models based on Efron’s technique and the
data samples are generated using S-Plus programme randomizer.
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Assessment of this method is investigated by performing simulation study on generated
data. Two simulation studies are carried out to confirm the suitability of the models.
Graph obtained from the results indicated that bootstrapping provides an alternative
method in constructing estimation for base hazard function. This method is good
alternative for a distribution-free approach with a minimal set of data. |
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