Raji Balasubramanian

Raji Balasubramanian

Education: 

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.

Research Description: 

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.

Publication List: 

PubMed Search Link

Key Publications: 

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, in press.

Xu, H., Gu, X., Tadesse, M. G., Balasubramanian, R. (2017). A modified Random Survival Forests algorithm for variable selection in the presence of imperfect self-reports or laboratory based diagnostic tests, Journal of Computational and Graphical Statistics, accepted.

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

Balasubramanian, R.*, Houseman, E. A.*, Coull, B. A., Lev, M. H., Schwamm, L. H., Betensky, R. A. (2014). Variable importance in matched case-control studies in settings of high-dimensional data, Journal of the Royal Statistical Society, Series C, 63(4), 639-655.

*equal contribution