Jerome P. Reiter

Jerome P. Reiter

Professor of Statistical Science

External address: 
212 Old Chem, Durham, NC 27708
Internal office address: 
Duke Box 90251, Durham, NC 27708-0251
Phone: 
(919) 668-5227

Overview

My primary research focus has been investigating statistical methods of preserving data confidentiality. More generally, I am interested in the analysis of complex surveys, especially missing data methods and causal inference. I enjoy collaborating on data analyses with researchers who are not statisticians, particularly in the social sciences. I also am the associate director of the Information Initiative at Duke (iiD).

Education & Training

  • Ph.D., Harvard University 1999

  • B.S., Duke University 1992

Selected Grants

Addressing Bias from Missing Data in EHR Based Studies of CVD awarded by National Institutes of Health (Collaborator). 2018 to 2023

Integrating Multiple Data Sources to Account for Nonignorable Nonresponse awarded by National Science Foundation (Principal Investigator). 2017 to 2019

CIF21 DIBBs: An Integrated System for Public/Private Access to Large-scale, Confidential Social Science Data awarded by National Science Foundation (Principal Investigator). 2015 to 2018

Computatopmal Methods and Tools for Creating High Quality, Public Use Census Microdata awarded by Alfred P. Sloan Foundation (Principal Investigator). 2016 to 2017

NCRN-MN:Triangle Census Research Network awarded by National Science Foundation (Principal Investigator). 2011 to 2016

TC:Large: Collaborative Research: Practical Privacy: Metrics and Methods for Protecting Record-level and Relational Data awarded by National Science Foundation (Principal Investigator). 2010 to 2016

Multiple Imputation Methods for Handling Missing Data in Longitudinal Studies with Refreshment Samples awarded by National Science Foundation (Principal Investigator). 2011 to 2014

Sharing Confidential Datasets With Geographic Identifiers Via Multiple Imputation awarded by National Institutes of Health (Principal Investigator). 2009 to 2012

MMS: Methodology for Improving Public Use Data Dissemination Via Multiply-Imputer, Partially Synthetic Data awarded by National Science Foundation (Principal Investigator). 2008 to 2011

Yu, H, and Reiter, JP. "Differentially private verification of regression predictions from synthetic data." Transactions on Data Privacy 11.3 (December 1, 2018): 279-297.

Wortman, JH, and Reiter, JP. "Simultaneous record linkage and causal inference with propensity score subclassification." Statistics in Medicine 37.24 (October 2018): 3533-3546. Full Text

Lott, A, and Reiter, JP. "Wilson Confidence Intervals for Binomial Proportions with Multiple Imputation for Missing Data." The American Statistician (May 17, 2018): 1-19. Full Text

Dalzell, NM, and Reiter, JP. "Regression Modeling and File Matching Using Possibly Erroneous Matching Variables." Journal of Computational and Graphical Statistics (April 19, 2018): 1-11. Full Text

Sadinle, M, and Reiter, J. "Sequential identification of nonignorable missing data mechanisms." Statistica Sinica (2018). Full Text

Kinney, SK, Reiter, J, and Miranda, J. "Improving the Synthetic Longitudinal Business Database." (February 1, 2014).

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