Jaya Satagopan, PhD

Attending Biostatistician

Jaya Satagopan, PhD

Office Phone

646-888-8234

Education

University of Wisconsin

Current Research Interests

Dr. Satagopan’s research program in statistical genetics/genomics focuses on developing and promoting the use of novel statistical techniques for discovering new cancer risk factors using Bayesian penalization techniques, understanding how the benefits of treatment and preventive interventions differ in relation to genomic markers through studies of gene-environment and gene-treatment interactions using parsimonious models, and developing risk stratification approaches to cancer treatment and prevention using dimension reduction techniques. She is the lead statistician of cancer molecular epidemiology studies of nevi, cognitive function in brain tumor patients and animal models of imaging and targeted treatment. She co-ordinates the department’s Quantitative Science Undergraduate Research Experience summer internship program with Drs. Elena Elkin and Kay See Tan, with assistance from Ms. Shireen Lewis. She also teaches the annual eight-week course Statistics for biomedical laboratory researchers for MSKCC’s postdoctoral researchers with Dr. Sujata Patil.

Publications

Selected peer-reviewed publications:


  1. Satagopan JM, Zhou Q, Oliveria SA, Dusza SW, Weinstock MA, Berwick M, Halpern AC (2011). Properties of preliminary test estimators and shrinkage estimators for evaluating multiple risk factors – Application to questionnaire data from the SONIC study. Journal of the Royal Statistical Society Series C (Applied Statistics), 60: 619 – 632.

  2. Satagopan JM, Elston RC (2013). Evaluation of removable statistical interaction for binary traits. Statistics in Medicine, 32: 1164-1190

  3. Satagopan JM, Sen A, Zhou Q, Lan Q, Rothman N, Langseth H, Engel LS (2015). Bayes and empirical Bayes methods for reduced rank regression models in matched case-control studies. Biometrics, 72: 584 – 595.

  4. Satagopan JM, Iasonos A (2017). Measuring differential treatment benefit across marker specific subgroups: the choice of outcome scale. Contemporary Clinical Trials, doi: 10.1016/j.cct.2017.02.007.

  5. Devlin SM, Satagopan JM (2017). Statistical interactions from a growth curve perspective. Human Heredity, 82: 21-36.

Visit PubMed for a full listing of Jaya Satagopan’s journal articles

Pubmed is an online index of biomedical articles maintained by the U.S. National Library of Medicine and the National Institutes of Health.