Center for Child & Family Policy | Duke University

Jerome P. Reiter

Mrs. Alexander Hehmeyer Associate Professor of Statistical Science and Affiliate of the Center for Child and Family Policy

Jerry Reiter is the Mrs. Alexander Hehmeyer Professor of Statistical Science at Duke University. Reiter participates in both applied and methodological research in statistical science. He is most interested in applications involving social science and public policy, although he enjoys working with researchers in all disciplines.

His methodological research focuses mainly on statistical methods for protecting data confidentiality, for handling missing data, and for modeling complex data, including methods for causal inferences. Reiter is the principal investigator of the Triangle Census Research Network, which is funded by the National Science Foundation to improve the practice of data dissemination among federal statistical agencies.

Reiter graduated from Duke with a BS in mathematics in 1992. He earned his Ph.D. in statistics from Harvard University in 1999. Reiter returned to Duke in 2002 in the Department of Statistical Science. In 2010, he was appointed a Bass Chair in recognition of "excellence in undergraduate teaching and research." In addition, he received the Alumni Distinguished Undergraduate Teaching Award in 2007. This annual award is given by Duke undergraduates to a member of the Duke faculty.

Research Interests:
Data and Survey Methods

Education:

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

Teaching Spring 2024:

• STA 790-1.01, SPECIAL TOPICS Synopsis
  Old Chem 025, TuTh 10:05 AM-11:20 AM
• STA 901S.01, STATISTICAL SCIENCE SEMINAR Synopsis
  Old Chem 116, F 03:05 PM-04:30 PM

Representative Publications   (More Publications)

1. Deng, Y; Hillygus, DS; Reiter, JP; Si, Y; Zheng, S (2013). Handling attrition in longitudinal studies: The case for refreshment samples. Statistical Science, 28(2), 238-256. [1306.2791v1], [doi]  [abs]


2. Burgette, LF; Reiter, JP (2012). Nonparametric Bayesian multiple imputation for missing data due to mid-study switching of measurement methods. Journal of the American Statistical Association, 107(498), 439-449. [doi]  [abs]


3. Kinney, SK; Reiter, JP; Reznek, AP; Miranda, J; Jarmin, RS; Abowd, JM (2011). Towards unrestricted public use business microdata: The synthetic Longitudinal Business Database. International Statistical Review, 79(3), 363-384. [doi]  [abs]


4. Drechsler, J; Reiter, JP (2010). Sampling with synthesis: A new approach for creating public use census microdata. Journal of the American Statistical Association, 105(492), 1323-1332. [doi]  [abs]


5. Kohnen, CN; Reiter, JP (2009). Multiple imputation for combining confidential data owned by two agencies. Journal of the Royal Statistical Society. Series A: Statistics in Society, 172(2), 511-528. [doi]  [abs]

Curriculum Vitae