Jerome P. Reiter

Jerome P. Reiter

Professor of Statistical Science

External address: 
214A Old Chem, Durham, NC 27708
Internal office address: 
Duke Box 90251, Durham, NC 27708-0251
Phone: 
(919) 668-5227

Overview

My primary areas of research include methods for preserving data confidentiality, for handling missing values, for integrating information across multiple sources, and for the analysis of surveys and causal studies. I enjoy collaborating on data analyses with researchers who are not statisticians, particularly in the social sciences and public policy.

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

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 2020

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

Kaufman, Brystana G., et al. “Use of Hospital Referral Regions in Evaluating End-of-Life Care..” J Palliat Med, Aug. 2019. Pubmed, doi:10.1089/jpm.2019.0056. Full Text

Akande, O., et al. “Imputation multiple de valeurs manquantes dans des données des ménages contenant des zéros structurels.” Survey Methodology, vol. 45, no. 2, June 2019, pp. 289–315.