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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

A computationally simple test of homogeneity of odds ratios for twin data

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Computationally simple accelerated failure time regression for interval censored data

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Local likelihood analysis of survival data with censored intermediate events

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Molecular subtypes of anaplastic oligodendroglioma : Implications for patient management at diagnosis

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Multivariate logistic regression for familial aggregation of two disorders. I. Development of models and methods

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Multivariate logistic regression for familial aggregation of two disorders. II. Analysis of studies of eating and mood disorders

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Nonparametric estimation in a cure model with random cure times

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Optimally selected chi square statistics for equivalence testing

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PTEN is a target of chromosome 10q loss in anaplastic oligodendrogliomas and PTEN alterations are associated with poor prognosis

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Tumor location and growth pattern correlate with genetic signature in oligodendroglial neoplasms

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α-synuclein occurs in lipid-rich high molecular weight complexes, binds fatty acids, and shows homology to the fatty acid-binding proteins

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Alternative derivations of a rule for early stopping in favor of H0

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Alternative derivations of a rule for early stopping in favor of HO

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Approximating the distribution of maximally selected McNemar's statistics

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Multiple imputation for simple estimation of the hazard function based on interval censored data

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On nonidentifiability and noninformative censoring for current status data

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Redistribution algorithms for censored data

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Shipment impairs lymphocyte proliferative responses to microbial antigens

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Simple approximations for the maximal transmission/disequilibrium test with a multi-allelic marker

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Two double-blinded, randomized, comparative trials of 4 Human Immunodeficiency Virus type 1 (HIV-1) envelope vaccines in HIV-1-infected individuals across a spectrum of disease severity : AIDS clinical trials groups 209 and 214

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Using conditional logistic regression to fit proportional odds models to interval censored data

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A non-parametric maximum likelihood estimator for bivariate interval censored data

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An extension of Kendall's coefficient of concordance to bivariate interval censored data

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Clinical trials using HIV-1 RNA-based primary endpoints : Statistical analysis and potential biases

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Local EM estimation of the hazard function for interval-censored data

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Contact

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