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Author Title Type [ Year(Asc)]
2014
Bradley, J.R.. "Survey Fusion for Data that Exhibit Multivariate, Spatio-Temporal Dependencies." In Joint Statistical Meetings 2014., 2014.
Eck, A., and L-K Soh. "Survey Informatics: Ideas, Opportunities, and Discussions." In UNL/SRAM/Gallup Symposium. Omaha, NE, 2014, available at http://grc.unl.edu/unlsramgallup-symposium.
Porter, A.T.. A Survey of Contemporary Spatial Models for Small Area Estimation., 2014.
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.
Crimi, N., and W. C. Eddy. "Top-Coding and Public Use Microdata Samples from the U.S. Census Bureau." Journal of Privacy and Confidentiality 6 (2014): 21-58, available at http://repository.cmu.edu/jpc/vol6/iss2/2/.
Friedline, T., P. Johnson, and R. Hughes. "Toward healthy balance sheets: Savings accounts as a gateway for young adults’ asset diversification and accumulation." The St. Louis Federal Reserve Bulletin (2014), available at http://research.stlouisfed.org/publications/review/2014/q4/friedline.pdf.
Bellman, B.. Towards an Understanding of Dynamics Between Race, Population Movement, and the Built Environment of American Cities (undergraduate honors thesis). University of Colorado at Boulder Undergraduate Honors Thesis, 2014.
Hudomiet, Peter. Twitter, Big Data, and Jobs Numbers, LSA Today. online, 2014, available at http://www.lsa.umich.edu/lsa/ci.twitterbigdataandjobsnumbers_ci.detail.
Folch, David C., Daniel Arribas-Bel, Julia Koschinsky, and Seth E. Spielman. Uncertain Uncertainty: Spatial Variation in the Quality of American Community Survey Estimates. University of Colorado at Boulder / University of Tennessee Preprint 1813:38122, 2014, available at http://hdl.handle.net/1813/38122.
McCutcheon, Allan L., K. Rao, and O. Kaminska. "The Untold Story of Multi-Mode (Online and Mail) Consumer Panels: From Optimal Recruitment to Retention and Attrition." In Online Panel Surveys: An Interdisciplinary Approach, edited by M. Callegaro, R. Baker, J. Bethlehem, A. Göritz, J. Krosnick and P. Lavrakas. Wiley, 2014.
Kimberlin, Sara, Jiyoun Kim, and Luke Shaefer. "An updated method for calculating income and payroll taxes from PSID data using the NBER’s TAXSIM, for PSID survey years 1999 through 2011." Unpublished manuscript, University of Michigan. Accessed May 6 (2014): 2016.
Cordova-Cazar, A.L., and R.F. Belli. "The use of paradata (in time use surveys) to better evaluate data 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.
Miranda, Javier, and Lars Vilhuber. Using partially synthetic data to replace suppression in the Business Dynamics Statistics: early results. Cornell University Preprint 1813:40852, 2014, available at http://hdl.handle.net/1813/40852.
Miranda, J., and L. Vilhuber. "Using Partially Synthetic Data to Replace Suppression in the Business Dynamics Statistics: Early Results." Privacy in Statistical Databases (2014): 232-242. DOI: 10.1007/978-3-319-11257-2_18, available at http://dx.doi.org/10.1007/978-3-319-11257-2_18.
Antenucci, Dolan, Michael J. Cafarella, Margaret C. Levenstein, Christopher Ré, and Matthew Shapiro. Using Social Media to Measure Labor Market Flows. Mimeo, 2014, available at http://www-personal.umich.edu/~shapiro/papers/LaborFlowsSocialMedia.pdf.
McCutcheon, A.L.. "Web Surveys, Online Panels, and Paradata: Automating Adaptive Design." In NSF-Census Research Network (NCRN) Spring Meeting. Washington, DC, 2014, available at http://www.ncrn.info/event/ncrn-meeting-spring-2014.
Al Baghal, T., R.F. Belli, A.L. Phillips, and N. Ruther. "What are You Doing Now? Activity Level Responses and Errors in the American Time Use Survey." Journal of Survey Statistics and Methodology 2, no. 4 (2014).
Karr, A. F.. "Why data availability is such a hard problem." Statistical Journal of the International Association for Official Statistics 30, no. 2 (2014).
Woodruff, A., V. Pihur, A. Acquisti, S. Consolvo, L. Schmidt, and L. Brandimarte. "Would a Privacy Fundamentalist Sell their DNA for \$1000... if Nothing Bad Happened Thereafter? A Study of the Western Categories, Behavior Intentions, and Consequences." In Proceedings of the Tenth Symposium on Usable Privacy and Security (SOUPS). New York, NY: ACM, 2014, available at https://www.usenix.org/conference/soups2014/proceedings/presentation/woodruff.
2013
Hu, J., R. Mitra, and J.P. Reiter. "Are independent parameter draws necessary for multiple imputation?" The American Statistician 67 (2013): 143-149. DOI: 10.1080/00031305.2013.821953, available at http://www.tandfonline.com/doi/full/10.1080/00031305.2013.821953.
Holan, S.H.. A Bayesian Approach to Estimating Agricultural Yield Based on Multiple Repeated Surveys, Institute of Public Policy and the Truman School of Public Affairs., 2013.
Steorts, Rebecca C., Rob Hall, and Stephen E. Fienberg. A Bayesian Approach to Graphical Record Linkage and De-duplication, arXiv. 1312.4645, 2013, available at https://arxiv.org/abs/1312.4645.
Cressie, N.. Bayesian inference for the Spatial Random Effects Model, Department of Statistics, Macquarie University. Macquarie University, 2013.
Banerjee, A., J. Murray, and D. B. Dunson. "Bayesian learning of joint distributions of objects." In Proceedings of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS) 2013., 2013, available at http://jmlr.csail.mit.edu/proceedings/papers/v31/banerjee13a.html.
Wu, G.. "Bayesian Modeling in the Era of Big Data: the Role of High-Throughput and High-Performance Computing." In The Extreme Science and Engineering Discovery Environment Conference. San Diego, CA, 2013.

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