Jerome P. Reiter

Professor of Statistical Science

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.

Appointments and Affiliations

  • Professor of Statistical Science
  • Chair of the Department of Statistical Science
  • Affiliate Faculty Member, Duke-Margolis Center for Health Policy
  • Affiliate of the Center for Child and Family Policy
  • Faculty Research Scholar of DuPRI's Population Research Center
  • Bass Fellow

Contact Information

  • Office Location: 214A Old Chem, Box 90251, Durham, NC 27708
  • Office Phone: +1 919 668 5227
  • Email Address: jreiter@duke.edu
  • Websites:

Education

  • B.S. Duke University, 1992
  • Ph.D. Harvard University, 1999

Awards, Honors, and Distinctions

  • Links Lecture Award. American Statistical Association. 2023
  • Clifford C. Clogg Memorial Lecture. Pennsylvania State University. 2022
  • Master’s in Interdisciplinary Data Science Distinguished Faculty Award. Duke University. 2020
  • Fellow of the Institute of Mathematical Statistics. Institute of Mathematical Statistics. 2020
  • Outstanding Postdoc Mentor Award. Duke University. 2016
  • Gertrude Cox Award. Washington Statistical Society and RTI International. 2014
  • W.J. Youden Award in Interlaboratory Testing. American Statistical Association. 2013
  • ASA Fellows. American Statistical Association. 2011
  • Alumni Distinguished Undergraduate Teaching Award. Duke University. 2007

Courses Taught

  • STA 996: Spring or Fall Internship
  • STA 995: Internship
  • STA 901S: Statistical Science Seminar
  • STA 891: Topics for Preliminary Exam Preparation in Statistical Science
  • STA 790-1: Special Topics in Statistics
  • STA 693: Research Independent Study
  • STA 582: Spring Proseminar
  • STA 522: Study Design: Design of Surveys and Causal Studies
  • STA 493: Research Independent Study
  • STA 393: Research Independent Study
  • STA 322: Study Design: Design of Surveys and Causal Studies
  • STA 211: The Mathematics of Regression

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