B.A., Mount Holyoke College, 1996; Sc.D. Harvard University, 2002; Postdoc, Harvard University
Area(s) of Specialization:
Metabolomic studies, pediatric HIV studies, measurement error in self-reported outcomes, study design, high dimensional data and analysis of biological networks.
My research is motivated by studies of complex disorders in large epidemiological studies such as the Women’s Health Initiative. My interests are in methods for biomarker discovery in metabolomics studies, biological network analysis and measurement error models.
Xu, H.*, Qian, J.*, Paynter, N. P., Zhang, X., Whitcomb, B. W., Tworoger, S. S., Rexrode, K. M., Hankinson, S. E., Balasubramanian, R. (2018): Estimating the area under the Receiver Operating Characteristic (ROC) curve in matched case control studies, Statistics in Medicine, accepted.
Xu, H., Gu, X., Tadesse, M. G., Balasubramanian, R. (2018). A modified Random Survival Forests algorithm for high dimensional predictors and self-reported outcomes, Journal of Computational and Graphical Statistics, in press.
Balasubramanian, R., Fowler, M.G., Dominguez, K., Lockman, S., Tookey, P. A., Huong, N. N. G., Nesheim, S., Hughes, M. D., Lallemant, M., Toswill, J., Shaffer, N., Sherman, G., Palumbo, P., Shapiro, D. E. (2017). The Association Of Prophylactic Maternal And Infant Antiretroviral Regimen With The Time To Positive HIV-1 DNA Polymerase Chain Reaction In Non-Breastfed Infants Infected Primarily With Non-B Subtype HIV-1 – A Multi Cohort Analysis, AIDS, 31(18), 2465-2474.
Gu, X., Balasubramanian, R. (2016). Study design for non-recurring, time to event outcomes in the presence of error-prone diagnostic tests or self-reports, Statistics in Medicine, 35(22), 3961-3975. PMCID: PMC5012924
Gu, X., Ma, Y., Balasubramanian, R. (2015). Semi-parametric time to event models in the presence of error-prone, self-reported outcomes - with application to the Women’s Health Initiative, Annals of Applied Statistics, 9 (2), 714-730. PMCID: PMC4729390