Rebecca A Betensky

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

Computationally simple estimation and improved efficiency for special cases of double truncation

Eliminating bias due to censoring in Kendall's tau estimators for quasi-independence of truncation and failure

Austin, M. D., & Betensky, R. A. (n.d.).

Publication year

2014

Journal title

Computational Statistics and Data Analysis

Volume

73

Page(s)

16-26

10.1016/j.csda.2013.11.018

Abstract

Abstract

While the currently available estimators for the conditional Kendall's tau measure of association between truncation and failure are valid for testing the null hypothesis of quasi-independence, they are biased when the null does not hold. This is because they converge to quantities that depend on the censoring distribution. The magnitude of the bias relative to the theoretical Kendall's tau measure of association between truncation and failure due to censoring has not been studied, and so its importance in real problems is not known. We quantify this bias in order to assess the practical usefulness of the estimators. Furthermore, we propose inverse probability weighted versions of the conditional Kendall's tau estimators to remove the effects of censoring and provide asymptotic results for the estimators. In simulations, we demonstrate the decrease in bias achieved by these inverse probability weighted estimators. We apply the estimators to the Channing House data set and an AIDS incubation data set.

Evidence-based decision support for neurological diagnosis reduces errors and unnecessary workup

Mild to moderate Alzheimer dementia with insufficient neuropathological changes

Synergistic effect of β-amyloid and neurodegeneration on cognitive decline in clinically normal individuals

Tau pathology does not affect experience-driven single-neuron and network-wide Arc/Arg3.1 responses

The effect of hospital care on early survival after penetrating trauma

Variable importance in matched case-control studies in settings of high dimensional data

Variable selection and prediction using a nested, matched case-control study: Application to hospital acquired pneumonia in stroke patients

An analysis of adaptive design variations on the sequential parallel comparison design for clinical trials

Differential relationships of reactive astrocytes and microglia to fibrillar amyloid deposits in alzheimer disease

Estimating the effect of emergency care on early survival after traffic crashes

Estimating Time to Disease Progression Comparing Transition Models and Survival Methods-An Analysis of Multiple Sclerosis Data

Examination of the clinicopathologic continuum of Alzheimer disease in the autopsy cohort of the national alzheimer coordinating center

Gene transfer of human Apoe isoforms results in differential modulation of amyloid deposition and neurotoxicity in mouse brain

Hospital Acquired Pneumonia Is Linked to Right Hemispheric Peri-Insular Stroke

Human miRNome profiling identifies microRNAs differentially present in the urine after kidney injury

Imperfect gold standards for biomarker evaluation

Waikar, S. S., Betensky, R. A., Emerson, S. C., & Bonventre, J. V. (n.d.).

Publication year

2013

Journal title

Clinical Trials

Volume

10

Issue

5

Page(s)

696-700

10.1177/1740774513497540

Abstract

Abstract

Background Serum creatinine has been used as the diagnostic test for acute kidney injury (AKI) for decades despite having imperfect sensitivity and specificity. Novel tubular injury biomarkers may revolutionize the diagnosis of KI; however, even if a novel tubular injury biomarker is 100% sensitive and 100% specific, it may appear inaccurate when using serum creatinine as the gold standard. Conclusions In general, the apparent diagnostic performance of a biomarker depends not only on its ability to detect injury but also on disease prevalence and the sensitivity and specificity of the imperfect gold standard. Apparent errors in diagnosis using a new biomarker may be a reflection of errors in the imperfect gold standard itself rather than poor performance of the biomarker. Clinical Trials 2013; 10: 696700. http://ctj.sagepub.com.

Improved design of prodromal Alzheimer's disease trials through cohort enrichment and surrogate endpoints

Interstitial fluid drainage is impaired in ischemic stroke and Alzheimer's disease mouse models

Molecular evolution of human adenoviruses

Patients with celiac disease have a lower prevalence of non-insulin-dependent diabetes mellitus and metabolic syndrome

Primary leptomeningeal lymphoma: International Primary CNS lymphoma collaborative group report

Reply to Sabanés Bové and Held's "Comment on Cai and Betensky (2003), On the Poisson Approximation for Hazard Regression"

Tau causes synapse loss without disrupting calcium homeostasis in the rTg4510 model of tauopathy