Type of Document	Dissertation
Author	Fan, Li
Author's Email Address	lf05@fsu.edu
URN	etd-08092009-010335
Title	Estimating The Probability Of Cardiovascular Disease: A Comparison Of Methods
Degree	Doctor of Philosophy
Department	Statistics, Department of
Advisory Committee	Advisor Name Title Daniel McGee Committee Chair Fred Huffer Committee Member Xufeng Niu Committee Member Myra Hurt Outside Committee Member
Keywords	Cardiovascular Disease Risk Prediction Logistic Cox PH Weibull VLDAFT
Date of Defense	2009-05-05
Availability	unrestricted
Abstract Risk prediction plays an important role in clinical medicine. It not only helps in educating patients to improve life style and in targeting individuals at high risk, but also guides treatment decisions. So far, various instruments have been used for different risk assessment in different countries and the risk predictions based from these different models are not consistent. In public use, a reliable risk prediction is necessary. This thesis discusses the models that have been developed for risk assessment and evaluates the performance of prediction at two levels, including the overall level and the individual level. At the overall level, cross validation and simulation are used to assess the risk prediction, while at the individual level, the "Parametric Bootstrap" and the delta method are used to evaluate the uncertainty of the individual risk prediction. Further exploration of the reasons producing different performance among the models is ongoing.
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