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2017
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.
2015
Carrig, M.M., D. Manrique-Vallier, K. Ranby, J.P. Reiter, and R. Hoyle. "A nonparametric, multiple imputation-based method for the retrospective integration of data sets." Multivariate Behavioral Research 50, no. 4 (2015): 383-397. DOI: 10.1080/00273171.2015.1022641, available at http://www.tandfonline.com/doi/full/10.1080/00273171.2015.1022641.
Si, Y., J.P. Reiter, and D.S. Hillygus. "Semi-parametric selection models for potentially non-ignorable attrition in panel studies with refreshment samples." Political Analysis 23 (2015): 92-112, available at http://pan.oxfordjournals.org/cgi/reprint/mpu009?%20ijkey=joX8eSl6gyIlQKP&keytype=ref.
Paiva, T., and J.P. Reiter. "Stop or continue data collection: A nonignorable missing data approach for continuous variables." ArXiv, no. 1511.02189 (2015), available at http://arxiv.org/abs/1511.02189.
2014
Manrique-Vallier, D., and J.P. Reiter. "Bayesian multiple imputation for large-scale categorical data with structural zeros." Survey Methodology 40 (2014): 125-134, available at http://www.stat.duke.edu/ jerry/Papers/SurvMeth14.pdf.
Hu, J., J.P. Reiter, and Q. Wang. "Disclosure risk evaluation for fully synthetic data." In Privacy in Statistical Databases, 185-199. Vol. 8744. Heidelberg: Springer, 2014.
Paiva, T., A. Chakraborty, J.P. Reiter, and A.E. Gelfand. "Imputation of confidential data sets with spatial locations using disease mapping models." Statistics in Medicine 33 (2014): 1928-1945.