[Andridge, R.R. and R.J.A. Little. 2011. “Proxy Pattern-Mixture Analysis for Survey Nonresponse.” Journal of Official Statistics 27: 153–180.]Search in Google Scholar
[Andridge, R.R. and K.J. Thompson. 2015. “Assessing Nonresponse Bias in a Business Survey: Proxy Pattern-Mixture Analysis for Skewed Data.” Annals of Applied Statistics 9(4): 2237–2265. Doi: http://dx.doi.org/10.1214/15-AOAS878.10.1214/15-AOAS878]Open DOISearch in Google Scholar
[Atrostic, B.K., N. Bates, and A. Silberstein. 2001. “Nonresponse in US Government Household Surveys: Consistent Measures, Recent Trends, and New Insights.” Journal of Official Statistics 17: 209–226.]Search in Google Scholar
[Bureau of Labor Statistics. 2015. Handbook of Methods. “Job Openings and Labor Turnover Survey” Chapter 18. Available at: https://www.bls.gov/opub/hom/pdf/homch18.pdf (accessed October 2017).]Search in Google Scholar
[Davis, W.R. and N. Pihama. 2009. “Survey Response as Organisational Behaviour: an Analysis of the Annual Enterprise Survey, 2003–2007.” New Zealand Association of Economists Conference. New Zealand: New Zealand Association of Economists. Available at: http://ro.uow.edu.au/eispapers/826/ (accessed October 2017).]Search in Google Scholar
[De Heer, W. and E. De Leeuw. 2002. “Trends in Household Survey Nonresponse: a Longitudinal and International Comparison.” In Survey Nonresponse, edited by R.M. Groves, D.A. Dillman, J.L. Eltinge, and R.J.A. Little, 41–54. New York: John Wiley and Sons.]Search in Google Scholar
[Dillman, D.A. 2000. Mail and Internet Surveys: The Tailored Design Method (second edition). New York: John Wiley & Sons.]Search in Google Scholar
[Dillman, D.A., J.D. Smyth, and L.M. Christian. 2009. Internet, Phone, Mail, and Mixed-Mode Surveys: the Tailored Design Method (third edition). Hoboken, NJ: John Wiley & Sons.]Search in Google Scholar
[Freedman, D.S., A. Thornton, and D. Camburn. 1980. “Maintaining Response Rates in Longitudinal Studies.” Sociological Methods & Research 9: 87–98.10.1177/004912418000900104]Search in Google Scholar
[Groves, R.M. 2006. “Nonresponse Rates and Nonresponse Bias in Household Surveys.” Public Opinion Quarterly 70: 646–675.10.1093/poq/nfl033]Search in Google Scholar
[Groves, R.M., D.A. Dillman, J.L. Eltinge, and R.J.A. Little. 2002. Survey Nonresponse. New York: John Wiley and Sons.]Search in Google Scholar
[Heberlein, T.A. and R. Baumgartner. 1978. “Factors Affecting Response Rates to Mailed Questionnaires: A Quantitative Analysis of the Published Literature.” American Sociological Review 43: 447–462.10.2307/2094771]Search in Google Scholar
[Holbrook, A., J.A. Krosnick, and A. Pfent. 2007. “The Causes and Consequences of Response Rates in Surveys by the News Media and Government Contractor Survey Research Firms.” In Advances in Telephone Survey Methodology, edited by J.M. Lepkowski, C. Tucker, J.M. Brick, E. De Leeuw, L. Japec, P.J. Lavrakas, M.W. Link and R.L. Sangster, 499–528. Hoboken, NJ: Wiley.10.1002/9780470173404.ch23]Search in Google Scholar
[Hothorn, T., K. Hornik, and A. Zeileis. 2006. “Unbiased Recursive Partitioning: a Conditional Inference Framework.” Journal of Computational and Graphical Statistics 15: 651–674.10.1198/106186006X133933]Search in Google Scholar
[Janik, F. and S. Kohaut. 2012. “Why Don’t They Answer? Unit Nonresponse in the IAB Establishment Panel.” Quality & Quantity 46: 917–934.10.1007/s11135-011-9436-y]Search in Google Scholar
[Kreuter, F., K. Olson, J. Wagner, T. Yan, T.M. Ezzati-Rice, C. Casas-Cordero, M. Lemay, A. Peytchev, R.M. Groves, and T.E. Raghunathan. 2010. “Using Proxy Measures and Other Correlates of Survey Outcomes to Adjust for Non-Response: Examples from Multiple Surveys.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 173: 389–407.10.1111/j.1467-985X.2009.00621.x]Search in Google Scholar
[Lepkowski, J.M. and M.P. Couper. 2002. “Nonresponse in the Second Wave of Longitudinal Household Surveys.” In Survey Nonresponse, edited by R.M. Groves, D.A. Dillman, J.L. Eltinge, and R.J.A. Little, 259–272. New York: John Wiley and Sons.]Search in Google Scholar
[Little, R.J.A. and S. Vartivarian. 2005. “Does Weighting for Nonresponse Increase the Variance of Survey Means?” Survey Methodology 31: 161–168.]Search in Google Scholar
[Lohr, S., V. Hsu, and J. Montaquila. 2015. “Using Classification and Regression Trees to Model Survey Nonresponse.” In Joint Statistical Meetings, Proceedings of the Survey Research Methods Section: American Statistical Association. 2071–2085. Alexandria, VA: American Statistical Association. Available at: http://ww2.amstat.org/sections/srms/Proceedings/y2015f.html (accessed October 2017).]Search in Google Scholar
[Morgan, J.N. and J.A. Sonquist. 1963. “Problems in the Analysis of Survey Data, and a Proposal.” Journal of the American Statistical Association 58: 415–434.10.1080/01621459.1963.10500855]Search in Google Scholar
[Office of Management and Budget. 2006. Statistical Directive No. 2, Standards and Guidelines for Statistical Surveys 2006. Washington DC: OMB. Available at: https://obamawhitehouse.archives.gov/sites/default/files/omb/inforeg/statpolicy/standards_stat_surveys.pdf (accessed October 2017).]Search in Google Scholar
[Paxson, M.C., D.A. Dillman, and J. Tarnai. 1995. “Improving Response to Business Mail Surveys.” In Business Survey Methods, edited by B.G. Cox, D.A. Binder, B.N. Chinnappa, A. Christianson, M.J. Colledge, and P.S. Kott, 303–316. New York: John Wiley and Sons.10.1002/9781118150504.ch17]Search in Google Scholar
[Phipps, P. and D. Toth. 2012. “Analyzing Establishment Nonresponse Using an Interpretable Regression Tree Model with Linked Administrative Data.” The Annals of Applied Statistics 6: 772–794.10.1214/11-AOAS521]Search in Google Scholar
[Särndal, C. 2011. “The 2010 Morris Hansen Lecture. Dealing with Survey Nonresponse in Data Collection, in Estimation.” Journal of Official Statistics 27(1): 1–21.]Search in Google Scholar
[Särndal, C. and P. Lundquist. 2014. “Accuracy in Estimation with Nonresponse: A Function of Degree of Imbalance and Degree of Explanation.” Journal of Survey Statistics and Methodology 2(4): 361–387. Doi: https://doi.org/10.1093/jssam/smu014.10.1093/jssam/smu014]Open DOISearch in Google Scholar
[Schouten, B., F. Cobben, and J. Bethlehem. 2009. “Indicators for the Representativeness of Survey Response.” Survey Methodology 35(1): 101–113.]Search in Google Scholar
[Schouten, B., N. Shlomo, and C. Skinner. 2011. “Indicators for Monitoring and Improving Representativeness of Response.” Journal of Official Statistics 27(2): 231–253.]Search in Google Scholar
[Seiler, C. 2010. Dynamic Modelling of Nonresponse in Business Surveys. No. 93. Ifo Working Paper. Available at: https://econpapers.repec.org/paper/cesifowps/_5f93.htm (accessed October 2017).]Search in Google Scholar
[Singer, E. 2002. “The Use of Incentives to Reduce Nonresponse in Household Surveys.” In Survey Nonresponse, edited by R.M. Groves, D.A. Dillman, J.L. Eltinge, and R.J.A. Little, 163–177. New York: John Wiley and Sons.]Search in Google Scholar
[Smaill, K. 2012. “Trajectory Modelling of Longitudinal Non-Response in Business Surveys.” Statistical Journal of the International Association of Official Statistics 28: 137–144.]Search in Google Scholar
[Su, X., M. Wang, and J. Fan. 2004. “Maximum Likelihood Regression Trees.” Journal of Computational and Graphical Statistics 13: 586–598.10.1198/106186004X2165]Search in Google Scholar
[Tomaskovic-Devey, D., J. Leiter, and S. Thompson. 1994. “Organizational Survey Nonresponse.” Administrative Science Quarterly 39: 439–457.10.2307/2393298]Search in Google Scholar
[Toth, D. 2017. rpms: Recursive Partitioning for Modeling Survey Data. R package version 0.2.0. Available at: https://CRAN.R-project.org/package=rpms (accessed October 2017).10.32614/CRAN.package.rpms]Search in Google Scholar
[Wagner, J. 2010. “The Fraction of Missing Information as a Tool for Monitoring the Quality of Survey Data.” Public Opinion Quarterly 74: 223–243. Doi: http://dx.doi.org/10.1093/poq/nfq007.10.1093/poq/nfq007]Open DOISearch in Google Scholar
[Wagner, J. 2012. “A Comparison of Alternative Indicators for the Risk of Nonresponse Bias.” Public Opinion Quarterly 76: 555–575. Doi: http://dx.doi.org/10.1093/poq/nfs032.10.1093/poq/nfs032627697530538342]Open DOISearch in Google Scholar
[Watson, N. and M. Wooden. 2009. “Identifying Factors Affecting Longitudinal Survey Response.” In Methodology of Longitudinal Surveys, edited by Peter Lynn, 151–181. Hoboken, NJ: John Wiley and Sons.10.1002/9780470743874.ch10]Search in Google Scholar