Fangya Mao, PhD
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Fangya Mao
PhD
Assistant Professor
Biostatistics; time-to-event and multistate data analysis; risk prediction; latent variable analysis, multivariate analysis; data integration; cost-effective study designs for biomarker discovery; chronic disease epidemiology; cancer prevention; target trial emulation
My research focuses on developing statistical methods for complex biomedical and epidemiologic data, with an emphasis on time-to-event and multistate processes, risk prediction, latent variable and multivariate analysis, and data integration. I develop cost-effective study designs, including two-phase designs, for biomarker discovery and disease progression research. My methodological work is motivated by applications in cancer epidemiology and prevention, chronic disease research, and target trial emulation using observational data. My research aims to develop practical and efficient statistical approaches to better understand disease natural history, identify risk factors and biomarkers, improve risk prediction, and inform clinical and public health decision-making.
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