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Author Title [ Type(Desc)] Year
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Book Chapter
Karr, A. F., and J. P. Reiter. "Analytical frameworks for data release: A statistical view." In Confidentiality and Data Access in the Use of Big Data: Theory and Practical Approaches. New York City, NY: Cambridge University Press, 2014.
Journal Article
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.
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, J. P., T. Schifeling, and M. De Yoreo. "Data fusion for correcting measurement errors." (Submitted).
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.
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.
De Yoreo, M., J. P. Reiter, and D. S. Hillygus. "Nonparametric Bayesian models with focused clustering for mixed ordinal and nominal data." Bayesian Analysis (2015). DOI: 10.1214/16-BA1020.
Kim, H. J., J. P. Reiter, and A. F. Karr. "Simultaneous edit-imputation and disclosure limitation for business establishment data." Journal of Applied Statistics (2016). DOI: 10.1080/02664763.2016.1267123.
Paiva, T., and J. P. Reiter. "Stop or continue data collection: A nonignorable missing data approach for continuous variables." Journal of Official Statistics (2017).
Kinney, S. K., J. P. Reiter, and J. Miranda. "SynLBD 2.0: Improving the Synthetic Longitudinal Business Database." Statistical Journal of the International Association for Official Statistics 30 (2014): 129-135.
Report
Fosdick, B. K., Maria DeYoreo, and J. P. Reiter. Categorical data fusion using auxiliary information. arXiv 1506.05886, 2015, available at http://arxiv.org/abs/1506.05886.