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1.
Atrostic, B., N. Bates, G. Burt, and A. Silberstein. 2001. “Nonresponse in US Government Household Surveys: Consistent Measures, Recent Trends, and New Insights.” Journal of Official Statistics 17: 209–226.
2.
Bates, N. and K. Creighton. 2000. “The Last Five Percent: What Can We Learn from Difficult/Late Interviews?” In Proceedings of the Section on Government Statistics and the Section on Social Statistics: American Statistical Association, 2000: 120–125, Washington, DC. Available at: https://s3.amazonaws.com/sitesusa/wp-content/uploads/sites/242/2014/05/IHSNG-asa2000proceedings.pdf (accessed April 2017).
3.
Beaumont, J., C. Bocci, and D. Haziza. 2014. “An Adaptive Data Collection Procedure for Call Prioritization.” Journal of Official Statistics 30: 607–621. Doi: http://dx.doi.org/10.2478/jos-2014-0040.
4.
Bethlehem, J., F. Cobben, and B. Schouten. 2011. Handbook of Nonresponse in Household Surveys . Hoboken, NJ: Wiley.
5.
Biemer, P. and L. Lyberg. 2003. Introduction to Survey Quality . Hoboken, NJ: Wiley.
6.
Billiet, J., M. Philippens, R. Fitzgerald, and I. Stoop. 2007. “Estimation of Non-Response Bias in the European Social Survey: Using Information from Reluctant Respondents.” Journal of Official Statistics 23: 135–162.
7.
Brick, J.M. and D. Williams. 2013. “Explaining Rising Nonresponse Rates in Cross-Sectional Surveys.” The Annals of the American Academy of Political and Social Science 645: 36–59. Doi: http://dx.doi.org/10.1177/0002716212456834.
8.
Couper, M. 1998. “Measuring Survey Quality in a CASIC Environment.” In Proceedings of the Section on Survey Research Methods: American Statistical Association, 1998: 41–49, Washington, DC.
9.
Curtin, R., S. Presser, and E. Singer. 2000. “The Effect of Response Rate Changes on the Index of Consumer Sentiment.” Public Opinion Quarterly 64: 413–428. Doi: http://dx.doi.org/10.1093/poq/nfi002.
10.
Curtin, R., S. Presser, and E. Singer. 2005. “Changes in Telephone Survey Nonresponse over the Past Quarter Century.” Public Opinion Quarterly 64: 87–98. Doi: http://dx.doi.org/10.1093/poq/nfi002.
11.
de Leeuw, E. 2005. “To Mix or Not to Mix Data Collection Modes in Surveys.” Journal of Official Statistics 21: 233–255.
12.
de Leeuw, E. and W. de Heer. 2002. “Trends in Household Survey Nonresponse: a Longitudinal and International Comparison.” In Survey Nonresponse , edited by R. Groves, D. Dillman, J. Eltinge, and R. Little, 41–54. New York, NY: Wiley.
13.
Deming, W. 1953. “On a Probability Mechanism to Attain an Economic Balance between the Resultant Error of Response and Bias of Nonresponse.” Journal of the American Statistical Association 48: 743–772.
14.
Efron, B. and R. Tibshirani. 1993. An Introduction to the Bootstrap . New York, NY: Chapman and Hall.
15.
El-Badry, M. 1956. “A Sampling Procedure for Mailed Questionnaires.” Journal of the American Statistical Association 51: 209–227. Doi: http://dx.doi.org/10.1080/01621459.1956.10501321.
16.
Elliott, M., R. Little, and S. Lewitzky. 2000. “Subsampling Callbacks to Improve Survey Efficiency.” Journal of the American Statistical Association 95: 730–738. Doi: http://dx.doi.org/10.2307/2669453.
17.
Filion, F. 1976. “Exploring and Correcting for Nonresponse Bias Using Follow-Ups of Nonrespondents.” Pacific Sociological Review 19: 401–408. Doi: 10.2307/1388756.
18.
Fuller, W. 1975. “Regression Analysis for Sample Survey.” Sankhyā 37, Series C, Pt. 3: 117–132.
19.
Graham, J., A. Olchowski, and T. Gilreath. 2007. “How Many Imputations Are Really Needed? Some Practical Clarifications of Multiple Imputation Theory.” Prevention Science 8: 206–213. Doi: http://dx.doi.org/10.1007/s11121-007-0070-9.
20.
Groves, R. and S. Heeringa. 2006. “Responsive Design for Household Surveys: Tools for Actively Controlling Survey Errors and Costs.” Journal of the Royal Statistics Society: Series A (Statistics in Society) 169: 439–457. Doi: http://dx.doi.org/10.1111/j.1467-985X.2006.00423.x.
21.
Hansen, M. and W. Hurwitz. 1946. “The Problem of Nonresponse in Sample Surveys.” Journal of the American Statistical Association 41: 517–529.
22.
Heeringa, S., B. West, and P. Berglund. 2010. Applied Survey Data Analysis . Boca Raton, FL: Taylor & Francis.
23.
Izrael, D., D. Hoaglin, and M. Battaglia. 2000. “A SAS Macro for Balancing a Weighted Sample.” In Proceedings of the SAS Users Group International (SUGI) Conference, Cary, NC: SAS Institute Inc. 1350–1355. Available at: http://www2.sas.com/proceedings/sugi25/25/st/25p258.pdf (accessed April 2017).
24.
Jacoby, J. and M. Matell. 1971. “Three-Point Likert Scales are Good Enough.” Journal of Marketing Research 8: 495–500.
25.
Kalton, G. and I. Flores-Cervantes. 2003. “Weighting Methods.” Journal of Official Statistics 19: 81–97.
26.
Keeter, S., C. Kennedy, M. Dimock, J. Best, and P. Craighill. 2006. “Gauging the Impact of Growing Nonresponse on Estimates from a National RDD Telephone Survey.” Public Opinion Quarterly 70: 759–779. Doi: http://dx.doi.org/10.1093/poq/nfl035.
27.
Kreuter, F. 2013. Improving Surveys with Paradata: Analytic Uses of Process Information . Hoboken, NJ: Wiley.
28.
Kreuter, F. and C. Casas-Cordero. 2010. “Paradata.” Working Paper 136. RatSWD Working Paper Series. Available at: http://www.ratswd.de/download/RatSWD_WP_2010/RatSWD_WP_136.pdf (accessed April 2017).
29.
Lewis, T. 2014. Testing for Phase Capacity in Surveys with Multiple Waves of Nonrespondent Follow-Up . PhD Thesis. University of Maryland, College Park. Doi: http://dx.doi.org/10.13016/M2WW46.
30.
Lewis, T. 2015. “Multivariate Tests for Phase Capacity.” Paper presented at the 2015 FedCASIC Workshops, Washington, DC. Available at: http://www.census.gov/fedcasic/fc2015/ppt/05_lewis.pdf (accessed April 2017).
31.
Lin, I.-F. and N. Schaeffer. 1995. “Using Survey Participants to Estimate the Impact of Nonparticipation.” Public Opinion Quarterly 59: 236–258. Doi: http://dx.doi.org/10.1086/269471.
32.
Little, R. and D. Rubin. 2002. Statistical Analysis with Missing Data . Second Edition . New York, NY: Wiley.
33.
Little, R. and S. Vartivarian. 2005. “Does Weighting for Nonresponse Increase the Variance of Survey Means?” Survey Methodology 31: 161–168.
34.
McPhee, C. and S. Hastedt. 2012. “More Money? The Impact of Larger Incentives on Response Rates in a Two-Phase Mail Survey.” In Proceedings from the Federal Committee on Statistical Methodology (FCSM) Research Conference. Washington, DC. Available at: https://s3.amazonaws.com/sitesusa/wp-content/uploads/sites/242/2014/05/Hastedt_2012FCSM_I-A.pdf (accessed April 2017).
35.
O’Quigley, J., M. Pepe, and L. Fisher. 1990. “Continual Reassessment Method: A Practical Design for Phase 1 Clinical Trials in Cancer.” Biometrics 46: 33–48. Doi: http://dx.doi.org/10.2307/2531628.
36.
Peytchev, A., R. Baxter, and L. Carley-Baxter. 2009. “Not All Survey Effort Is Equal: Reduction of Nonresponse Bias and Nonresponse Error.” Public Opinion Quarterly 73: 785–806. Doi: http://dx.doi.org/10.1093/poq/nfp037.
37.
Politz, A. and W. Simmons. 1949. “An Attempt to Get the Not-at-Homes into the Sample without Callbacks.” Journal of the American Statistical Association 44: 9–16. Doi: http://dx.doi.org/10.1080/01621459.1949.10483288.
38.
Potthoff, R., K. Manton, and M. Woodbury. 1993. “Correcting for Nonavailability Bias in Surveys Weighting Based on the Number of Callbacks.” Journal of the American Statistical Association 88: 1197–1207. Doi: http://dx.doi.org/10.1080/01621459.1993.10476399.
39.
Raghunathan, T., J. Lepkowski, J. Van Hoewyk, and P. Solenberger. 2001. “A Multivariate Technique for Multiply Imputing Missing Values Using a Sequence of Regression Models.” Survey Methodology 27: 85–95.
40.
Rao, R., M. Glickman, and R. Glynn. 2004. “Use of Covariates and Survey Wave to Adjust for Nonresponse.” Biometrical Journal 46: 579–588. Doi: http://dx.doi.org//10.1002/bimj.200310049.
41.
Rao, R., M. Glickman, and R. Glynn. 2008. “Stopping Rules for Surveys with Multiple Waves of Nonrespondent Follow-Up.” Statistics in Medicine 27: 2196–2213. Doi: http://dx.doi.org/10.1002/sim.3063.
42.
Rubin, D. 1987. Multiple Imputation for Nonresponse in Surveys . New York, NY: Wiley.
43.
Rubin, D. and N. Schenker. 1986. “Multiple Imputation for Interval Estimation from Simple Random Samples with Ignorable Nonresponse.” Journal of the American Statistical Association 81: 366–374. Doi: http://dx.doi.org/10.1080/01621459.1986.10478280.
44.
Rust, K. 1985. “Variance Estimation for Complex Estimators in Sample Surveys.” Journal of Official Statistics 1: 381–397.
45.
Schenker, N., T. Raghunathan, P.-L. Chiu, D. Makuc, G. Zhang, and A. Cohen. 2006. “Multiple Imputation of Missing Income Data in the National Health Interview Survey.” Journal of the American Statistical Association 101: 924–933. Doi: http://dx.doi.org/10.1198/016214505000001375.
46.
Schouten, B. and N. Schlomo. 2015. “Selecting Adaptive Survey Design Strata with Partial R-Indicators.” International Statistical Review , Online First Edition. Doi: http://dx.doi.org/10.1111/insr.12159.
47.
Sigman, R., T. Lewis, N. Yount, and K. Lee. 2014. “Does The Length of Fielding Period Matter? Examining Response Scores of Early versus Late Responders.” Journal of Official Statistics 30: 651–674. Doi: https://doi.org/10.2478/jos-2014-0042.
48.
Tourangeau, R. and T. Plewes (eds.). 2013. Nonresponse in Social Science Surveys: A Research Agenda . Washington, DC: The National Academies Press. Available at: http://www.nap.edu/read/18293/chapter/1 (accessed April 2017).
49.
Valliant, R. 2004. “The Effect of Multiple Weighting Steps on Variance Estimation.” Journal of Official Statistics 20: 1–18.
50.
U.S. Office of Personnel Management (OPM). 2015. “2015 Federal Employee Viewpoint Survey Technical Report.” Available at: http://www.fedview.opm.gov/2015FILES/2015_OPM_Technical_Report.pdf (accessed April 2017).
51.
Wagner, J. 2008. Adaptive Survey Design to Reduce Nonresponse Bias . PhD Thesis. University of Michigan, Ann Arbor.
52.
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.
53.
Wagner, J. and T. Raghunathan. 2010. “A New Stopping Rule for Surveys.” Statistics in Medicine 29: 1014–1024. Doi: http://dx.doi.org/10.1002/sim.3834.
54.
Wolter, K. 2007. Introduction to Variance Estimation . Second Edition . New York, NY: Springer.
55.
Woodruff, R. 1971. “A Simple Method for Approximating the Variance of a Complicated Estimate.” Journal of the American Statistical Association 66: 411–414. Doi: http://dx.doi.org/10.2307/2283947.
