How to Obtain Valid Inference under Unit Nonresponse?

Bethlehem, J., F. Cobben, and B. Schouten. 2011. Handbook of Nonresponse in Household Surveys, volume 568 of Wiley Handbooks in Survey Methodology. John Wiley & Sons, Inc., Hoboken, New Jersey.10.1002/9780470891056Search in Google Scholar

Boeschoten, L., D. Oberski, and T. de Waal. 2016. “Estimating Classification Error under Edit Restrictions in Combining Survey-Register Data.” Journal of Official Statistics 33:921–962. Doi: http://dx.doi.org/10.1515/JOS-2017-0044.10.1515/JOS-2017-0044Open DOISearch in Google Scholar

Cohn, N. 2016. “How One 19-Year-Old Illinois Man is Distorting National Polling Averages.” The New York Times. Available at: https://nyti.ms/2k5sB5z (accessed September 26, 2017).Search in Google Scholar

De Waal, T., J. Pannekoek, and S. Scholtus. 2011. Handbook of Statistical Data Editing and Imputation, volume 563 of Wiley Handbooks in Survey Methodology. John Wiley & Sons, Inc., Hoboken, New Jersey.10.1002/9780470904848Search in Google Scholar

Deville, J.-C. and C.-E. Särndal. 1992. “Calibration Estimators in Survey Sampling.” Journal of the American statistical Association 87: 376–382.10.1080/01621459.1992.10475217Search in Google Scholar

Groves, R.M., F.J. Fowler, Jr, M.P. Couper, J.M. Lepkowski, E. Singer, and R. Tourangeau. 2009. Survey Methodology, volume 561 of Wiley Series in Survey Methodology. John Wiley & Sons, Inc., Hoboken, New Jersey.Search in Google Scholar

Horvitz, D.G. and D.J. Thompson. 1952. “A Generalization of Sampling without Replacement from a Finite Universe.” Journal of the American Statistical Association 47: 663–685.10.1080/01621459.1952.10483446Open DOISearch in Google Scholar

Howard, W.J. 2012. Using Principal Component Analysis (pca) to Obtain Auxiliary Variables for Missing Data in Large Data Sets. University of Kansas. PhD Dissertation.Search in Google Scholar

Lumley, T. 2014. Analysis of Complex Survey Samples. Available at: http://cran.r-project.org/web/packages/survey/survey.pdf (accessed September 26, 2017).Search in Google Scholar

Manrique-Vallier, D. and J.P. Reiter. 2016. “Bayesian Simultaneous Edit and Imputation for Multivariate Categorical Data.” Journal of the American Statistical Association. Doi: http://dx.doi.org/10.1080/01621459.2016.1231612.10.1080/01621459.2016.1231612Open DOISearch in Google Scholar

Peytchev, A. 2012. “Multiple Imputation for Unit Nonresponse and Measurement Error.” Public Opinion Quarterly 76: 214–237. Doi: https://doi.org/10.1093/poq/nfr065.10.1093/poq/nfr065Open DOISearch in Google Scholar

R Core Team. 2015. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.Search in Google Scholar

Rubin, D.B. 1976. “Inference and Missing Data.” Biometrika 63: 581–592.10.1093/biomet/63.3.581Open DOISearch in Google Scholar

Rubin, D.B. 1987. Multiple Imputation for Nonresponse in Surveys. Wiley series in probability and mathematical statistics. John Wiley & Sons, New York, USA.10.1002/9780470316696Search in Google Scholar

Rubin, D.B. 1996. “Multiple Imputation after 18+ Years.” Journal of the American Statistical Association 91: 473–489.10.1080/01621459.1996.10476908Open DOISearch in Google Scholar

Särndal, C., B. Swensson, and J. Wretman. 1992. Model Assisted Survey Sampling. Springer Series in Statistics. Springer-Verlag.10.1007/978-1-4612-4378-6Search in Google Scholar

Schulte Nordholt, E., J. van Zeijl, and L. Hoeksma. 2014. Dutch Census 2011, Analysis and Methodology. The Hague/Heerlen. Available at: https://www.cbs.nl/NR/rdonlyres/5FDCE1B4-0654-45DA-8D7E-807A0213DE66/0/2014b57pub.pdf (accessed 26 September 2017).Search in Google Scholar

Stapleton, L.M. 2008. “Analysis of Data from Complex Surveys.” In International Handbook of Survey Methodology, edited by E.D. De Leeuw, J.J. Hox, and D. Dillman, 342–369. Psychology Press, Taylor & Francis Group, New York.Search in Google Scholar

Van Buuren, S. 2012. Flexible Imputation of Missing Data. CRC press, Boca Raton, Florida.10.1201/b11826Search in Google Scholar

Van Buuren, S. and K. Groothuis-Oudshoorn. 2011. “mice: Multivariate Imputation by Chained Equations in R.” Journal of Statistical Software 45: 1–67. Doi: http://dx.doi.org/10.18637/jss.v045.i03.10.18637/jss.v045.i03Open DOISearch in Google Scholar

Vink, G. and S. van Buuren. 2014. “Pooling Multiple Imputations when the Sample Happens to be the Population.” arXiv preprint arXiv:1409.8542. Available at: https://arxiv.org/pdf/1409.8542.pdf (accessed 26 September 2017).Search in Google Scholar

Zhang, L.-C. 2012. “Topics of Statistical Theory for Register-Based Statistics and Data Integration.” Statistica Neerlandica 66: 41–63.10.1111/j.1467-9574.2011.00508.xOpen DOISearch in Google Scholar

Zhou, H., M.R. Elliott, and T.E. Raghunathan. 2016. “A Two-Step Semiparametric Method to Accommodate Sampling Weights in Multiple Imputation.” Biometrics 72: 242–252.10.1111/biom.12413605897526393409Open DOISearch in Google Scholar