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Rebecca A Betensky

Rebecca Betensky

Rebecca Betensky

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Chair of the Department of Biostatistics

Professor of Biostatistics

Professional overview

Prior to NYU, Dr. Betensky was Professor of Biostatistics at the Harvard T.H. Chan School of Public Health. She was director of the Harvard Catalyst (Clinical and Translational Science Award) Biostatistics Program; director of the Data and Statistics Core for the Massachusetts Alzheimer’s Disease Research Center; and director of the Biostatistics Neurology Core at Massachusetts General Hospital. Previously, she was the Biostatistics Program Leader for the Dana-Farber/Harvard Cancer Center.

Dr. Betensky’s research focuses on methods for the analysis of censored and truncated outcomes and covariates, which frequently arise from the subsampling of cohort studies. She has a long-time interest in clinical trials, and has written on the evaluation of biomarkers and the use and interpretation of p-values. She has collaborated extensively in studies in neurologic diseases, and serves as statistical editor for Annals of Neurology.

Dr. Betensky was awarded, and directed for 15 years, an NIH T32 training program in neurostatistics and neuroepidemiology for pre- and post-doctoral students in biostatistics and epidemiology and for clinician-scientists. She previously directed Harvard’s Biostatistics programs to promote and support diversity at all levels in the field of quantitative public health. She was also a member of the BMRD Study Section for review of NIH statistical methodology grants; on committees for the Institute of Medicine; and a co-chair of the technical advisory committee for the scientific registry of transplant recipients.

Dr. Betensky an elected Fellow of the American Statistical Association and of the International Statistical Institute, and is a past recipient of the Spiegelman Award from the American Public Health Association. She currently serves as a member of the Board of Scientific Counselors for Clinical Science and Epidemiology at the National Cancer Institute.

Education

AB, Mathematics, Harvard University, Cambridge, MA
PhD, Statistics, Stanford University, Stanford, CA

Areas of research and study

Biology
Biostatistics
Neuroepidemiology
Neurology
Neurostatistics
Translational science

Publications

Publications

Maximally selected χ2 statistics for k x 2 tables

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Predictive value of CD19 measurements for bacterial infections in children infected with human immunodeficiency virus

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Thymocyte development in Ah-receptor-deficient mice is refractory to TCDD-inducible changes

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A boundary crossing probability for the bessel process

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A boundary crossing probability for the Bessel process

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Construction of a continuous stopping boundary from an alpha spending function

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Effect of shipment, storage, anticoagulant, and cell separation on lymphocyte proliferation assays for human immunodeficiency virus-infected patients

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Multiple imputation for early stopping of a complex clinical trial

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An examination of methods for sample size recalculation during an experiment

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Conditional power calculations for early acceptance of H(O) embedded in sequential tests

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Early stopping to accept H(o) based on conditional power : Approximations and comparisons

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Local estimation of smooth curves for longitudinal data

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Sequential analysis of censored survival data from three treatment groups

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An analysis of correlated multivariate binary data : Application to familial cancers of the ovary and breast

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An O'Brien-Fleming sequential trial for comparing three treatments

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Low-grade, latent prostate cancer volume : Predictor of clinical cancer incidence?

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Actual versus ideal weight in the calculation of surface area : Effects on dose of 11 chemotherapy agents

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A  transformation model for smoothed estimation from interval-censored data

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Increased blood-brain barrier permeability following COVID-19 and its correlation with Alzheimer’s biomarkers

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Pathways to Personalized Medicine - Embracing Heterogeneity for Progress in ClinicalTherapeutics Research in Alzheimer's Disease

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Post hoc selection of a method for multiplicity adjustment of secondary and exploratory endpoints

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Pseudo-observation regression for sequentially truncated data

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Social Determinants of Health Predict Brain MRI Severity in Pediatric Onset MultipleSclerosis

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 Design and analysis of N-of-1 trials that incorporate sequential monitoring

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Contact

rebecca.betensky@nyu.edu 708 Broadway New York, NY, 10003