people

Jerome P Reiter

Associate Professor of Statistical Science
CCFP Faculty Fellow

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 director of the Data Services Core of the Social Science Research Institute at Duke. The Core assists researchers in the social sciences with statistical, computational, and data-based needs.

Research Interests

• sociology
• psychology
• public policy
• education
• economics

Education:

• PhD Harvard University - 1999
• BS Duke University - 1992

Representative Publications   (More Publications)

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


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


3. Kohnen CN and Reiter JP (2009). Multiple imputation for combining confidential data owned by two agencies. Journal of the Royal Statistical Society, Series A, 172, 511 - 528.


4. Reiter JP (2008). Multiple imputation when records used for imputation are not used or disseminated for analysis. Biometrika, 95, 933 - 946.


5. Reiter JP and Raghunathan TE (2007). The multiple adaptations of multiple imputation. Journal of the American Statistical Association, 102, 1462 - 1471.

1. Some approaches and challenges in secure statistical analysis, SAMSI workshop on National Defense and Homeland Security, September, 2005
2. Methods for secure computation and data integration, Joint Statistical Meetings, August, 2005
3. Generating partially synthetic data when there are missing data, CS-Statistics Workshop on Privacy and Confidentiality, July, 2005
4. Disclosure Limitation via Synthetic Multiply-Imputed Datasets, International Conference on the Future of Statistical Theory, Practice, and Education, December, 2004
5. Disclosure Limitation via Synthetic Multiply-Imputed Datasets, Research Triangle Institute Fellows Symposium, December, 2004

Curriculum Vitae