Jaya Satagopan’s research focuses on statistical genetics/genomics with applications in cancer epidemiology and tumor biology studies. Her research topics include cost-effective study designs for genome-wide studies, estimating the lifetime risk of cancer in mutation carriers, dimension reduction and Bayesian shrinkage analysis methods for evaluating multiple disease risk factors, and methods for evaluating gene-exposure interactions.
She established the Center for South Asian Quantitative Health and Education at Rutgers. The center studies the risk of cancer and allied diseases and determinants of risk in South Asian communities and develops health communications aimed at promoting cancer prevention, control, and care in these communities.
Satagopan has investigated parsimonious risk models for evaluating cancer risk factors. She showed that sometimes multiplicative statistical interactions between risk factors may be required in risk models to obtain a good fit to the data, and certain types of interactions can be removed by modeling the outcome on a suitable scale, thus resulting in parsimonious additive models for risk. She has developed methods for evaluating additive statistical interactions between biomarkers and treatments in relation to time-to-event endpoints and applied these to digitally extracted data from phase III clinical trials of metastatic melanoma and metastatic colorectal cancer.
She received a Ph.D. in statistics from University of Wisconsin-Madison and a master’s degree in science communication and public engagement from University of Edinburgh.
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