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Powell, R.J., and A. Kirchner. "Achieving balance: Understanding the relationship between complexity and response quality." In American Association for Public Opinion Research 2014 Annual Conference. Anaheim, CA, 2014, available at http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx.
Porter, A. T., S.H. Holan, C.K. Wikle, and N. Cressie. "Spatial Fay-Herriot Models for Small Area Estimation with Functional Covariates." Spatial Statistics 10 (2014): 27-42, available at http://arxiv.org/pdf/1303.6668v3.pdf.
Porter, A.T., S.H. Holan, and C.K. Wikle. "Bayesian Semiparametric Hierarchical Empirical Likelihood Spatial Models." Journal of Statistical Planning and Inference 165 (2015): 78-90. DOI: 10.1016/j.jspi.2015.04.002.
Porter, A.T.. Big Data Methodology Applied to Small Area Estimation., 2014.
Porter, A.T., and J. Oleson. "A CAR model for multiple outcomes on mismatched lattices." Spatial and Spatio-Temporal Epidemiology 11 (2014): 79-88. DOI: 10.1016/j.sste.2014.08.001, available at http://www.sciencedirect.com/science/article/pii/S1877584514000604.
Porter, A.T.. "Flexible Bayesian Methodology for Multivariate Spatial Small Area Estimation." In Joint Statistical Meetings 2014. Boston, MA, 2014.
Porter, A.T.. Spatial Fay-Herriot Models for Small Area Estimation with Functional Covariates., 2013.
Porter, A.T.. "Flexible Semiparametric Hierarchical Spatial Models." In Joint Statistical Meetings 2013. Montreal, Canada, 2013.
Porter, A.T., C.K. Wikle, and S.H. Holan. "Small Area Estimation via Multivariate Fay-Herriot Models With Latent Spatial Dependence." Australian & New Zealand Journal of Statistics 57 (2015): 15-29, available at http://arxiv.org/abs/1310.7211.
Porter, A.T., S.H. Holan, and C.K. Wikle. "Multivariate Spatial Hierarchical Bayesian Empirical Likelihood Methods for Small Area Estimation." STAT 4, no. 1 (2015): 108-116. DOI: 10.1002/sta4.81, available at http://dx.doi.org/10.1002/sta4.81.
Porter, A.T.. A Survey of Contemporary Spatial Models for Small Area Estimation., 2014.
Phillips, A. L., T. Al Baghal, and R. F. Belli. "Troubles with time-use: Examining potential indicators of error in the ATUS." In Midwest Association for Public Opinion Research 2012 Annual Conference. Chicago, IL, 2012, available at http://www.mapor.org/conferences.html.
Phillips, A.L., T. Al Baghal, and R.F. Belli. "Troubles with time-use: Examining potential indicators of error in the American Time Use Survey." In American Association for Public Opinion Research 2013 Annual Conference. Boston, MA, 2013, available at http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx.
Perry, Benjamin, Venkata Kambhampaty, Kyle Brumsted, Lars Vilhuber, and William Block. Presentation: NADDI 2015: Crowdsourcing DDI Development: New Features from the CED2AR Project. Cornell University Preprint 1813:40172, 2015, available at http://hdl.handle.net/1813/40172.
Perry, Benjamin, Venkata Kambhampaty, Kyle Brumsted, Lars Vilhuber, and William Block. Collaborative Editing of DDI Metadata: The Latest from the CED2AR Project. Cornell University Preprint 1813:38200, 2014, available at http://hdl.handle.net/1813/38200.
Peer, E., J. Vosgerau, and A. Acquisti. "Reputation as a Sufficient Condition for Data Quality on Amazon Mechanical Turk." Behavior Research Methods 46 (2014): 1023-1031.
Peer, E., A. Acquisti, and S. Shalvi. "I Cheated, but only a Little–Partial Confessions to Unethical Behavior." Journal of Personality and Social Psychology 106 (2014): 202-217.
Parker, Jennifer. NCRN Meeting Fall 2014: Geographic linkages between National Center for Health Statistics’ population health surveys and air quality measures. NCRN Coordinating Office Preprint 1813:37412, 2014, available at http://hdl.handle.net/1813/37412.
Paiva, T., and J. P. Reiter. "Stop or continue data collection: A nonignorable missing data approach for continuous variables." Journal of Official Statistics (2017).
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.
Paiva, Thais, and Jerry Reiter. NCRN Meeting Spring 2014: Imputation of multivariate continuous data with non-ignorable missingness. NCRN Coordinating Office Preprint 1813:36399, 2014, available at http://hdl.handle.net/1813/36399.
Paiva, Thais. Multiple Imputation Methods for Nonignorable Nonresponse, Adaptive Survey Design, and Dissemination of Synthetic Geographies (Ph.D. thesis), Department of Statistical Sciences. Vol. Ph.D. Duke University phd, 2014, available at http://dukespace.lib.duke.edu/dspace/handle/10161/9406.
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.