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Dissertation & Master's Defenses

Upcoming Dissertation Defenses

Epidemiology Dissertation Defense
Jingchuan Guo-Blood Pressure & CVD Disease in Type 1 Diabetes: Exploration of Prediction & Control Epidemiology Dissertation Defense
Jingchuan Guo-Blood Pressure & CVD Disease in Type 1 Diabetes: Exploration of Prediction & Control
Tue 12/11/2018 9:00AM - 11:00AM


Defense location:
3512 Fifth Avenue, second floor conference room

Tue 12/11/2018
EOH Dissertation Defense
Hsiu-Chi Ting - How organisms lacking oxidizable lipids utilize lipid peroxidation for signaling: .. EOH Dissertation Defense
Hsiu-Chi Ting - How organisms lacking oxidizable lipids utilize lipid peroxidation for signaling: ..
Thu 12/13/2018 12:00PM - 2:00PM
4140 Public Health, Young Seminar Room

Title of the dissertation: "How organisms lacking oxidizable lipids utilize lipid peroxidation for signaling: lipidomics approach."

Advisor: Valerian E. Kagan, PhD, DSc, Professor, Department of Environmental and Occupational Health

Committee members and departments:

Bruce R. Pitt, PhD, Professor, Department of Environmental and Occupational Health

Hülya Bayır, MD, Professor, Departments of Critical Care Medicine and Environmental and Occupational Health

Joel S. Greenberger, MD, FACRO, FACR, Professor and Chairman, Department of Radiation Oncology


Thu 12/13/2018
Biostatistics Dissertation Defense
Xingyuan Li - TBA Biostatistics Dissertation Defense
Xingyuan Li - TBA
Fri 1/18/2019 1:00PM - 3:00PM
7139 Public Health, Peterson Seminar Room

Xingyuan Li of the Department of Biostatistics defends her dissertation on "TBA".


Fri 1/18/2019

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Biostatistics Dissertation Defense

Yi Liu: Novel Test Procedures for Large-scale Bivariate Time-to-event Data on Single and...

Friday 7/28 1:00PM - 3:00PM
7139 Public Health, Peterson Seminar Room

Yi Liu of the Department of Biostatistics defends her dissertation on "Novel Test Procedures for Large-scale Bivariate Time-to-event Data on Single and Gene-based Markers, with an Application to a Genetic Study of AMD Progression"

Graduate faculty of the University and all other interested parties are invited to attend


ABSTRACT:

Motivated by a genome-wide association study (GWAS) to discover risk variants for the progression of Age-related Macular degeneration (AMD), I develop a computationally efficient copula-based score test, in which the association between bivariate progression times is explicitly modeled. Specifically, a two-step estimation approach with numerical derivatives to approximate the score function and information matrix is proposed. Both parametric and weakly parametric marginal distributions under the proportional hazards assumption are considered. Further I extend this work to gene-based tests through the functional linear smoothing approach, which models the variants (within the same gene region) as a function of their physical positions. A robust variance approach under functional linear model framework for bivariate variance adjustment is also been proposed. In both works, simulation studies were conducted to evaluate the Type I error control and power performance of the proposed method. Finally, we apply our method on a large randomized trial data, Age-related Eye Disease Study (AREDS), to identify susceptible risk variants and gene regions for AMD progression. The top variants identified in CFH and ARMS2 gene on Chromosome 1 and 10 show differential progression profiles for different genetic groups, which are useful in characterizing and predicting the risk of progression for patients with moderate AMD.

Last Updated On Monday, October 23, 2017 by Valenti, Renee Nerozzi
Created On Friday, June 09, 2017

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