Guoqing Diao’s research focuses on the development of new statistical methodologies and novel computational tools for solving important scientific problems arising in biomedical studies. His current research interests include semiparametric models, survival analysis, statistical genetics, longitudinal data analysis, diagnostic medicine, high-dimensional data analysis, clinical trials designs, and computational probability. His applied work includes collaborations with investigators in the areas of disability and rehabilitation, and policing and criminology. His research was/is funded by the National Institutes of Health, the National Science Foundation and industry.
2014 - 2019 Design Consistent and Non-Inferiority Multiple Region Clinical Trial. Funded by University of North Carolina/Amgen.
2018 - 2019 Academic Research Collaboration between GMU and UNC/Merck. Funded by University of North Carolina/Merck.
2017 - 2019 Academic Research Collaboration between Otsuka and GMU. Funded by Otsuka.
2011 - 2014 Statistical Inference for Random Recursive Equations. Funded by National Science of Foundation.
2010 - 2013 ARRA: Statistical Methods in Cancer Research. Funded by National Institutes of Health.
2007 - 2012 Statistical Methods in Current Cancer Research. Funded by University of North Carolina/National Institutes of Health.
2008 - 2008 Medicaid Quality Indicators for People with Disabilities. Funded by U.S. Department of Education.
Longitudinal Data Analysis
High-Dimensional Data Analysis
Clinical Trial Designs