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Jerome P. Reiter, Interim Dean of Natural Science

Jerome P. Reiter
Contact Info:
Office Location:  214A Old Chem, Box 90251, Durham, NC 27708
Email Address:   send me a message
Web Page:   http://www2.stat.duke.edu/~jerry/


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

Missing Data Imputation
Data and Survey Methods
Sampling and Survey Methods
Statistical Disclosure Limitation
Causal Inference
Research Interests: Data confidentiality, Analysis of complex surveys, MIssing data methods, Causal inference

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 associate director of the Information Initiative at Duke (iiD).

Areas of Interest:

public policy

Curriculum Vitae
Representative Publications   (More Publications)

  1. Deng, Y; Hillygus, DS; Reiter, JP; Si, Y; Zheng, S, Handling attrition in longitudinal studies: The case for refreshment samples, Statistical Science, vol. 28 no. 2 (May, 2013), pp. 238-256, Institute of Mathematical Statistics [1306.2791v1], [doi[abs].
  2. Burgette, LF; Reiter, JP, Nonparametric Bayesian multiple imputation for missing data due to mid-study switching of measurement methods, Journal of the American Statistical Association, vol. 107 no. 498 (August, 2012), pp. 439-449, Informa UK Limited [doi[abs].
  3. Kinney, SK; Reiter, JP; Reznek, AP; Miranda, J; Jarmin, RS; Abowd, JM, Towards unrestricted public use business microdata: The synthetic Longitudinal Business Database, International Statistical Review, vol. 79 no. 3 (2011), pp. 363-384, WILEY [doi[abs].
  4. Drechsler, J; Reiter, JP, Sampling with synthesis: A new approach for creating public use census microdata, Journal of the American Statistical Association, vol. 105 no. 492 (2010), pp. 1323-1332, Informa UK Limited [doi[abs].
  5. Kohnen, CN; Reiter, JP, Multiple imputation for combining confidential data owned by two agencies, Journal of the Royal Statistical Society: Series a (Statistics in Society), vol. 172 no. 2 (April, 2009), pp. 511-528, WILEY [doi[abs].

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