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2017
Abowd, John M.. "How Will Statistical Agencies Operate When All Data Are Private." Journal of Privacy and Confidentiality 7, no. 3 (2017), available at http://repository.cmu.edu/jpc/vol7/iss3/1/.
2016
Green, Andrew. Hours Off the Clock. Cornell University Preprint 1813:52610, 2016, available at http://hdl.handle.net/1813/52610.
Fusaro, V., and Luke H. Shaefer. "How Should We Define Low-Wage Work? An Analysis Using the Current Population Survey." Monthly Labor Review (2016), available at http://www.bls.gov/opub/mlr/2016/article/pdf/how-should-we-define-low-wage-work.pdf.
Abowd, John M.. How Will Statistical Agencies Operate When All Data Are Private?. Cornell University Preprint 1813:44663, 2016, available at http://hdl.handle.net/1813/44663.
2015
Hudomiet, Peter. he role of occupation specific adaptation costs in explaining the educational gap in unemployment.. Mimeo, 2015, available at https://sites.google.com/site/phudomiet/Hudomiet-JobMarketPaper.pdf?attredirects=0.
Wikle, C.K.. "Hierarchcial models for uncertainty quantification: An overview." In Handbook of Uncertainty Quantification, edited by Ghanem, R., Higdon, D. and Owhadi, H.. Springer, 2015.
Wikle, C.K., and M.B. Hooten. "Hierarchical Agent-Based Spatio-Temporal Dynamic Models for Discrete Valued Data." In Handbook of Discrete-Valued Time Series, edited by R. Davis, S. Holan, R. Lund and N. Ravishanker. Boca Raton, FL.: Chapman and Hall/CRC Press, 2015, available at http://www.crcpress.com/product/isbn/9781466577732.
Holan, S.H., and C.K. Wikle. "Hierarchical Dynamic Generalized Linear Mixed Models for Discrete-Valued Spatio-Temporal Data." In Handbook of Discrete-Valued Time Series, edited by R. Davis, S. Holan, R. Lund and N Ravishanker. Boca Raton, FL: Chapman and Hall/CRC Press, 2015, available at http://www.crcpress.com/product/isbn/9781466577732.
Holan, S.H., and C.K. Wikle. "Hierarchical Dynamic Generalized Linear Mixed Models for Discrete--Valued Spatio-Temporal Data." In Handbook of Discrete--Valued Time Series., 2015.
Arab, A., M.B. Hooten, and C.K. Wikle. "Hierarchical Spatial Models." In Encyclopedia of Geographical Information Science. Springer, 2015.
Wildhaber, M.L., C.K. Wikle, E.H. Moran, C.J. Anderson, K.J. Franz, and R. Dey. "Hierarchical, stochastic modeling across spatiotemporal scales of large river ecosystems and somatic growth in fish populations under various climate models: Missouri River sturgeon example." Geological Society (2015).
Cressie, N., and E.L. Kang. "Hot enough for you? A spatial exploratory and inferential analysis of North American climate-change projections." Mathematical Geosciences (2015). DOI: 10.1007/s11004-015-9607-9, available at http://dx.doi.org/10.1007/s11004-015-9607-9.
Gelman, Michael, Shachar Kariv, Matthew D. Shapiro, Dan Silverman, and Steven Tadelis. How individuals smooth spending: Evidence from the 2013 government shutdown using account data. National Bureau of Economic Research, 2015.
2014
Gelman, M., S. Kariv, M.D. Shapiro, D. Silverman, and S. Tadelis. "Harnessing Naturally Occurring Data to Measure the Response of Spending to Income." Science 345, no. 11 (2014). DOI: 10.1126/science.1247727, available at http://www.sciencemag.org/content/345/6193/212.full.
Timm, A., K. Olson, and J.D. Smyth. "Having a Lasting Impact: The Effects of Interviewer Errors on Data Quality." In Midwest Association for Public Opinion Research Annual Conference. Chicago, IL, 2014, available at http://www.mapor.org/conferences.html.
Ventura, S., R. Nugent, and E. Fuchs. "Hierarchical Linkage Clustering with Distributions of Distances for Large Scale Record Linkage." In Privacy in Statistical Databases (Lecture Notes in Computer Science, edited by J. Domingo-Ferrer, 283-298. Vol. 8744. Springer, 2014.
Cochran, B., and J.D. Smyth. "Hours or Minutes: Does One Unit Fit All?" In Midwest Association for Public Opinion Research Annual Conference. Chicago, IL, 2014, available at http://www.mapor.org/conferences.html.
Bliss, Laura. How to Make a Better Map—Using Neuroscience. Citylab Online, 2014, available at http://www.citylab.com/design/2014/11/how-to-make-a-better-map-according-to-science/382898/.
2013
Deng, Yiting, Sunshine D. Hillygus, Jerome P. Reiter, Yajuan Si, and Siyu Zheng. "Handling Attrition in Longitudinal Studies: The Case for Refreshment Samples." Statist. Sci. 28 (2013): 238-256. DOI: 10.1214/13-STS414, available at http://dx.doi.org/10.1214/13-STS414.
Wu, G., S.H. Holan, and C.K. Wikle. "Hierarchical Bayesian Spatio-Temporal Conway-Maxwell Poisson Models with Dynamic Dispersion." Journal of Agricultural, Biological, and Environmental Statistics 18 (2013): 335-356. DOI: 10.1007/s13253-013-0141-2, available at http://link.springer.com/article/10.1007/s13253-013-0141-2.
Wikle, C., S. Holan, and N. Cressie. "Hierarchical Spatio-Temporal Models and Survey Research." Statistics Views (2013), available at http://www.statisticsviews.com/details/feature/4730991/Hierarchical-Spatio-Temporal-Models-and-Survey-Research.html.
Sengupta, A., and N. Cressie. "Hierarchical Statistical Modeling of Big Spatial Datasets Using the Exponential Family of Distributions." Spatial Statistics 4 (2013): 14-44. DOI: 10.1016/j.spasta.2013.02.002, available at http://www.sciencedirect.com/science/article/pii/S2211675313000055.
Cressie, N., S. Holan, and C. Wikle. How can survey estimates of small areas be improved by leveraging social-media data?, The Survey Statistician. 68, 2013, available at http://isi.cbs.nl/iass/N68.pdf.
2012
Wikle, C.K.. "Hierarchical General Quadratic Nonlinear Models for Spatio-Temporal Dynamics." In Red Raider Conference. Lubbock, TX: Texas Tech University, 2012.
Sengupta, A., and N. Cressie. Hierarchical Statistical Modeling of Big Spatial Datasets Using the Exponential Family of Distributions. The Ohio State University 879, 2012.

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