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Marinela Capanu, PhD

Associate Attending Biostatistician

Marinela Capanu, Associate Attending  Biostatistician

Office Phone



University of Florida

Current Research Interests

Dr. Capanu’s current research interests are in the development of optimized variable selection techniques. Dr. Capanu is also interested in the application of hierarchical models for epidemiologic studies to identify rare genetic variants that increase the risk of cancer. As part of her collaborative work, Dr. Capanu is involved in the statistical analysis of the Women’s Environment, Cancer, and Radiation Epidemiology (WECARE) Study. In collaboration with Dr. Jonine Bernstein, Dr. Capanu is conducting the analysis of the WECARE Genome-Wide Association Study to discover novel SNPs implicated in the development of contralateral breast cancer. Dr. Capanu is also involved in collaborations with the Gastrointestinal Oncology Service as well as with the Department of Radiology. She has been working with investigators of these groups on the design and analysis of prospective and retrospective studies.


Selected peer-reviewed publications:

  1. Booth J, Capanu M, Heigenhauser L (2005) Exact conditional p-value calculation for the quasi-symmetry model, Journal of Computational and Graphical Statistics, 14(3):716-725.

  2. Capanu M, Presnell B (2007) Misspecification Tests for Binomial and Beta-Binomial Models, Statistics in Medicine, 27(14):2536-2554

  3. Capanu M, Orlow I, Berwick M, Hummer AJ, Thomas DC, Begg CB (2008) The Use of Hierarchical Models for Estimating Relative Risks of Individual Genetic Variants: An Application to a Study of Melanoma, Statistics in Medicine, 27(11):1973-1992

  4. Capanu M, Begg CB (2011) Hierarchical Modeling for Estimating Relative Risks of Rare Genetic Variants: Properties of the Pseudo-Likelihood Method, Biometrics, 61:371-380

  5. Capanu M, Concannon P, Haile RW, Bernstein L, Malone KE, Lynch CF, Liang X, Teraoka SN, Diep AT, Thomas DC, Bernstein JL; The WECARE Study Collaborative Group, Begg CB (2011) Assessment of rare BRCA1 and BRCA2 variants of unknown significance using hierarchical modeling, Genetic Epidemiology, 35:389-397

For a complete list of publications: