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Submitted
Reiter, J. P., T. Schifeling, and M. De Yoreo. "Data fusion for correcting measurement errors." (Submitted).
Barrientos, A. F., A. Bolton, T. Balmat, J. P. Reiter, A. Machanavajjhala, Y. Chen, C. Kneifel, M. DeLong, and J. M. de Figueiredo. "A framework for sharing confidential research data, applied to investigating differential pay by race in the U. S. government." (Submitted).
T. White, Kirk, Jerome P. Reiter, and Amil Petrin. "Imputation in U.S. Manufacturing Data and Its Implications for Productivity Dispersion." Review of Economics and Statistics (Submitted). DOI: 10.1162/REST_a_00678 , available at http://www.mitpressjournals.org/doi/abs/10.1162/REST_a_00678.
Sadinle, Mauricio, and Jerome P. Reiter. "Sequential identification of nonignorable missing data mechanisms." Statistica Sinica (Submitted). DOI: 10.5705/ss.202016.0328.
2017
Chen, Y., A. Machanavajjhala, J. P. Reiter, and A. Barrientos. "Differentially private regression diagnostics." In IEEE International Conference on Data Mining., 2017.
Hu, Jingchen, Jerome P. Reiter, and Quanli Wang. "Dirichlet Process Mixture Models for Modeling and Generating Synthetic Versions of Nested Categorical Data." Bayesian Analysis (2017). DOI: 10.1214/16-BA1047, available at http://projecteuclid.org/euclid.ba/1485227030.
Weinberg, Daniel, John M. Abowd, Robert F. Belli, Noel Cressie, David C. Folch, Scott H. Holan, Margaret C. Levenstein, Kristen M. Olson, Jerome P. Reiter, Matthew D. Shapiro et al. Effects of a Government-Academic Partnership: Has the NSF-Census Bureau Research Network Helped Secure the Future of the Federal Statistical System?. NCRN Coordinating Office Preprint 1813:52650, 2017, available at http://hdl.handle.net/1813/52650.
Li, F., O. Akande, and J. P. Reiter. "An empirical comparison of multiple imputation methods for categorical data." The American Statistician 71, no. 2 (2017). DOI: 10.1080/00031305.2016.1277158, available at http://www.tandfonline.com/doi/full/10.1080/00031305.2016.1277158.
Sadinle, M., and J.P. Reiter. "Itemwise conditionally independent nonresponse modeling for incomplete multivariate data." Biometrika 104, no. 1 (2017): 207-220. DOI: 10.1093/biomet/asw063, available at https://doi.org/10.1093/biomet/asw063.
Sadinle, M., and J. P. Reiter. "Itemwise conditionally independent nonresponse modeling for multivariate categorical data." Biometrika 104 (2017): 207-220.
Murray, J. S., and J. P. Reiter. "Multiple imputation of missing categorical and continuous outcomes via Bayesian mixture models with local dependence." Journal of the American Statistical Association 111, no. 516 (2017): 1466-1479.
Paiva, T., and J. P. Reiter. "Stop or continue data collection: A nonignorable missing data approach for continuous variables." Journal of Official Statistics (2017).
2016
McClure, D., and J. P. Reiter. "Assessing disclosure risks for synthetic data with arbitrary intruder knowledge." Statistical Journal of the International Association for Official Statistics 32, no. 1 (2016): 109-126. DOI: 10.3233/SJI-160957, available at http://content.iospress.com/download/statistical-journal-of-the-iaos/sji957.
Si, Y., J. P. Reiter, and D. S. Hillygus. "Bayesian latent pattern mixture models for handling attrition in panel studies with refreshment samples." Annals of Applied Statistics 10 (2016): 118-143. DOI: 10.1214/15-AOAS876, available at http://projecteuclid.org/euclid.aoas/1458909910.
DeYoreo, Maria, and Jerome P. Reiter. Bayesian mixture modeling for multivariate conditional distributions. ArXiv 1606.04457, 2016, available at http://arxiv.org/abs/1606.04457.
Manrique-Vallier, Daniel, and Jerome P. Reiter. "Bayesian Simultaneous Edit and Imputation for Multivariate Categorical Data." Journal of the American Statistical Association (2016). DOI: 10.1080/01621459.2016.1231612, available at http://dx.doi.org/10.1080/01621459.2016.1231612.
Fosdick, B. K., M. De Yoreo, and J. P. Reiter. "Categorical data fusion using auxiliary information." Annals of Applied Statistics 10 (2016): 1907-1929. DOI: 10.1214/16-AOAS925, available at http://projecteuclid.org/euclid.aoas/1483606845.
Reiter, Jerry. Differentially Private Verification of Regression Model Results. NCRN Coordinating Office Preprint 1813:52167, 2016, available at http://hdl.handle.net/1813/52167.
Schifeling, T. S., and J. P. Reiter. "Incorporating marginal prior information into latent class models." Bayesian Analysis 11 (2016): 499-518. DOI: doi:10.1214/15-BA959, available at https://projecteuclid.org/euclid.ba/1434649584.
Murray, Jared S., and Jerome P. Reiter. "Multiple Imputation of Missing Categorical and Continuous Values via Bayesian Mixture Models with Local Dependence." Journal of the American Statistical Association (2016). DOI: 10.1080/01621459.2016.1174132, available at http://dx.doi.org/10.1080/01621459.2016.1174132.
Redding, Stephen J., and David E. Weinstein. NCRN Meeting Fall 2016: Scanner Data and Economic Statistics: A Unified Approach. University of Michigan Preprint 1813:45821, 2016, available at http://hdl.handle.net/1813/45821.
Mccue, Kristin, John Abowd, Margaret Levenstein, Dhiren Patki, Ann Rodgers, Matthew Shapiro, and Nada Wasi. NCRN Meeting Spring 2016: Developing job linkages for the Health and Retirement Study. University of Michigan Preprint 1813:43895, 2016, available at http://hdl.handle.net/1813/43895.
Reiter, Jerry. NCRN Meeting Spring 2017: Differentially Private Verification of Regression Model Results. NCRN Coordinating Office Preprint 1813:52167, 2016, available at http://hdl.handle.net/1813/52167.
Vilhuber, Lars, Alan Karr, Jerome Reiter, John Abowd, and Jamie Nunnelly. NCRN Newsletter: Volume 2 - Issue 4. NCRN Coordinating Office Preprint 1813:42394, 2016, available at http://hdl.handle.net/1813/42394.
Vilhuber, Lars, Alan Karr, Jerome Reiter, John Abowd, and Jamie Nunnelly. NCRN Newsletter: Volume 3 - Issue 1. NCRN Coordinating Office Preprint 1813:44199, 2016, available at http://hdl.handle.net/1813/44199.

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