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
Faculty Research Scholar of DuPRI's Population Research Center
Faculty Network Member of The Energy Initiative
Affiliate Faculty Member, Duke-Margolis Center for Health Policy
Affiliate of the Center for Child and Family Policy
Bass Fellow

Contact Information

Office Location: 214A Old Chem, Box 90251, Durham, NC 27708
Email Address: jreiter@duke.edu
Websites:
- Personal site

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
Fellow of the Institute of Mathematical Statistics. Institute of Mathematical Statistics. 2020
Master’s in Interdisciplinary Data Science Distinguished Faculty Award. Duke University. 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 211: The Mathematics of Regression
STA 322: Study Design: Design of Surveys and Causal Studies
STA 393: Research Independent Study
STA 493: Research Independent Study
STA 522: Study Design: Design of Surveys and Causal Studies
STA 693: Research Independent Study
STA 891: Topics for Preliminary Exam Preparation in Statistical Science
STA 901S: Statistical Science Seminar
STA 993: Independent Study