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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.
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.
Hudomiet, Peter. Twitter, Big Data, and Jobs Numbers, LSA Today. online, 2014, available at http://www.lsa.umich.edu/lsa/ci.twitterbigdataandjobsnumbers_ci.detail.
Green, Andrew, Mark J. Kutzbach, and Lars Vilhuber. Two Perspectives on Commuting: A Comparison of Home to Work Flows Across Job-Linked Survey and Administrative Files. Cornell University Preprint 1813:52611, 2017, available at http://hdl.handle.net/1813/52611.
Steorts, Rebecca C., and Malay Ghosh. "Two-stage Bayesian benchmarking as applied to small area estimation." TEST 22, no. 4 (2013).
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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.
Gelman, Michael. "Understanding Household Consumption and Saving Behavior using Account Data." (forthcoming).
H. Shaefer, Luke, Kathryn Edin, and E. Talbert. "Understanding the Dynamics of $2-a-Day Poverty in the United States." The Russell Sage Foundation Journal of the Social Sciences 1, no. Severe Deprivation (2015).
Eck, A., S. Leen-Kiat, A. L. McCutcheon, J.D. Smyth, and R.F. Belli. "Understanding the Human Condition through Survey Informatics." IEEE Computer 48, no. 11 (2015): 112-116. DOI: 10.1109/MC.2015.327.
Chen, B., A. Shrivastava, and R. C. Steorts. Unique Entity Estimation with Application to the Syrian Conflict, arXiv. 1710.02690, 2017, available at https://arxiv.org/abs/1710.02690.
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.
Cordova-Cazar, A.L., and R.F. Belli. "The Use of Paradata to Evaluate Interview Complexity and Data Quality (in Calendar and Time Diary Surveys)." In 70th Annual Conference of the American Association for Public Opinion Research (AAPOR). Hollywood, Florida, 2015, available at http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx.
Stuart, Leonard Cleve. User Modeling via Machine Learning and Rule-based Reasoning to Understand and Predict Errors in Survey Systems. University of Nebraska-Lincoln Masters, 2013, available at http://digitalcommons.unl.edu/computerscidiss/70/.
Lee, Jinyoung, Ben Seloske, and Robert F. Belli. Using audit trails to evaluate an event history calendar survey instrument.
Belli, R. F.. Using behavior coding to understand respondent retrieval strategies that inform the structure of autobiographical knowledge.
Belli, R.F., L.D. Miller, L.-K. Soh, and T. Al Baghal. "Using Data Mining to Examine Interviewer-Respondent Interactions in Calendar Interviews." In 70th Annual Conference of the American Association for Public Opinion Research (AAPOR). Hollywood, Florida, 2015, available at http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx.
Belli, Robert F., Dee L. Miller, Tarek Al Baghal, and Leen-Kiat Soh. "Using Data Mining to Predict the Occurrence of Respondent Retrieval Strategies in Calendar Interviewing: The Quality of Retrospective Reports." Journal of Official Statistics 32, no. 3 (2016): 579-600. DOI: https://doi.org/10.1515/jos-2016-0030.
Spielman, S. E., and J. Logan. "Using High Resolution Population Data to Identify Neighborhoods and Determine their Boundaries." Annals of the Association of American Geographers 103 (2013): 67-84. DOI: 10.1080/00045608.2012.685049, available at http://www.tandfonline.com/doi/abs/10.1080/00045608.2012.685049.
Atkin, G., H. Arunachalam, A. Eck, D. Wettlaufer, L.-K. Soh, and R.F. Belli. "Using Machine Learning Techniques to Predict Respondent Type from A Priori Demographic Information." In 70th Annual Conference of the American Association for Public Opinion Research (AAPOR). Hollywood, Florida, 2015, available at http://www.aapor.org/AAPORKentico/Conference/Recent-Conferences.aspx.
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.
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.

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