Survival Analysis is a widely accepted approach to a large number of anthropological datasets that record time to event in the presence of drop-outs. In this thesis, we will give theoretical framework and illustration of Bayesian methodology in Survival Analysis. Such techniques as Kaplan-Meier estimation of survival function and Cox proportional hazard model will be presented through the prism of Bayesian inference. Illustrative datasets will be obtained from Professor Mary Shenk. The analysis will be conducted in SAS.
|Commitee:||Safer, Alan, Suaray, Kagba|
|School:||California State University, Long Beach|
|Department:||Mathematics and Statistics|
|School Location:||United States -- California|
|Source:||MAI 58/02M(E), Masters Abstracts International|
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