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EPI/BIO Seminar Series: Ying Zhang, PhD

3/7/2012 | Noon - 1 pm
Bellet Building, Room 604
  • Event Type: Lecture
  • Department: Epidemiology and Biostatistics
  • Speakers: Ying Zhang, PhD
  • Audiences: Current Students , General

"Classification with Multiple Tests without a Gold Standard"

This work investigates a general problem of combining multiple continuous tests without any gold standard or a reference test motivated by determination of GBV-C E2 antibody in HIV patients for a HIV/AIDS study conducted in the University of Iowa. The existing methods for combining
multiple tests are thoroughly studied and the optimal composite classification rules corresponding to the methods are developed to incorporate the situation that no gold standard for E2 antibody exists. The proposed methods are theoretically justified and numerically compared via extensive simulation studies. Finally, the methods are applied to the motivating example to determine the HIV patients who had
GBV-C E2 antibody that is hypothesized to prolong the survival from HIV infection.

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Ying Zhang, PhD
Dr. Zhang received his PhD in Statistics from the Department of Statistics at the University of Washington in 1998. He is currently a full professor in the Department of Biostatistics at the University of Iowa. His statistical methodology research covers the areas of survival and longitudinal data analysis for observational studies, clinical trial design, non/semi-parametric models, statistical computing and data mining and his current scientific collaboration research includes HIV/AIDS studies, large observational studies of Parkinson and Huntington diseases, cardiovascular diseases, and injury research of collegiate athletes.
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