[Andridge, R.H. and Little, R.J. (2011). Proxy Pattern-Mixture Analysis for Survey Nonresponse. Journal of Official Statistics, 27, 153-180.]Search in Google Scholar
[Atrostic, B.K., Bates, N., Burt, G., and Silberstein, A. (2001). Nonresponse in U.S. Government Household Surveys: Consistent Measures, Recent Trends, and New Insights. Journal of Official Statistics, 17, 209-226.]Search in Google Scholar
[Bartholomew, D.J. (1961). A Method of Allowing for ‘Not-at-Home’ Bias in Sample Surveys. Applied Statistics, 10, 52-59.10.2307/2985408]Search in Google Scholar
[Bates, N., Dahlhamer, J., and Singer, E. (2008). Privacy Concerns, too Busy, or Just not Interested: Using Doorstep Concerns to Predict Survey Nonresponse. Journal of Official Statistics, 24, 591-612.]Search in Google Scholar
[Beaumont, J.F. (2005). On the Use of Data Collection Process Information for the Treatment of Unit Nonresponse Through Weight Adjustment. Survey Methodology, 31, 227-231.]Search in Google Scholar
[Bethlehem, J.G. (1988). Reduction of Nonresponse Bias Through Regression Estimation. Journal of Official Statistics, 4, 251-260.]Search in Google Scholar
[Bethlehem, J.G. (2002). Weighting Nonresponse Adjustments Based on Auxiliary Information. Survey Nonresponse, R.M. Groves, D.A. Dillman, J.L. Eltinge, and R.J.A. Little (eds). New York: Wiley.]Search in Google Scholar
[Bethlehem, J., Cobben, F., and Schouten, B. (2011). Handbook in Nonresponse in Household Surveys. New York: Wiley.10.1002/9780470891056]Search in Google Scholar
[Brehm, J. (1993). The Phantom Respondents: Opinion Surveys and Political Representation. Ann Arbor: University of Michigan Press.]Search in Google Scholar
[Brick, J.M. and Jones, M.E. (2008). Propensity to Respond and Nonresponse Bias. Metron-International Journal of Statistics, LXVI, 51-73.]Search in Google Scholar
[Brick, J.M. and Kalton, G. (1996). Handling Missing Data in Survey Research. Statistical Methods in Medical Research, 5, 215-238.10.1177/096228029600500302]Search in Google Scholar
[Brick, J.M. and Montaquila, J.M. (2009). Nonresponse and Weighting. Handbook of Statistics. Sample Surveys: Design, Methods, and Applications, D. Pfeffermann and C.R. Rao (eds). Vol. 29A. Amsterdam: Elsevier-North Holland, 163-186.10.1016/S0169-7161(08)00008-4]Search in Google Scholar
[Brick, J.M., Montaquila, J., Han, D., and Williams, D. (2012). Improving Response Rates for Spanish-Speakers in Two-Phase Mail Surveys. Public Opinion Quarterly, 76, 721-732.10.1093/poq/nfs050]Search in Google Scholar
[Brick, J.M. and Williams, D. (2013). Explaining Rising Nonresponse Rates in Cross- Sectional Surveys. The ANNALS of the American Academy of Political and Social Science, 645, 36-59.10.1177/0002716212456834]Search in Google Scholar
[Cassel, C., Särndal, C.-E., and Wretman, J. (1983). Some Uses of Statistical Models in Connection With the Nonresponse Problem. Incomplete Data in Sample Surveys, W.G. Madow and I. Olkin (eds). Vol. 3. New York: Academic Press.]Search in Google Scholar
[Chang, T. and Kott, P.S. (2008). Using Calibration Weighting to Adjust for Nonresponse Under a Plausible Model. Biometrika, 95, 557-571.10.1093/biomet/asn022]Search in Google Scholar
[Cochran, W. (1977). Sampling Techniques, (3rd edition). New York: Wiley.]Search in Google Scholar
[Colley, R.H. (1945). Don’t Look Down Your Nose at Mail Questionnaires. Printers’ Ink, March, 16, 21-108.]Search in Google Scholar
[Curtin, R., Presser, S., and Singer, E. (2000). The Effects of Response Rate Changes on the Index of Consumer Sentiment. Public Opinion Quarterly, 64, 413-428.10.1086/31863811171024]Search in Google Scholar
[Curtin, R., Presser, S., and Singer, E. (2005). Changes in Telephone Survey Nonresponse Error Over the Past Quarter Century. Public Opinion Quarterly, 69, 87-98.10.1093/poq/nfi002]Search in Google Scholar
[Da Silva, D.N. and Opsomer, J.D. (2004). Properties of the Weighting Cell Estimator Under a Nonparametric Response Mechanism. Survey Methodology, 30, 45-55.]Search in Google Scholar
[Da Silva, D.N. and Opsomer, J.D. (2009). Nonparametric Propensity Weighting for Survey Nonresponse Through Local Polynomial Regression. Survey Methodology, 35, 165-176. ]Search in Google Scholar
[Dalenius, T. (1983). Some Reflections on the Problem of Missing Data. Incomplete Data in Sample Surveys, W.G. Madow and I. Olkin (eds). Vol. 3. New York: Academic Press, 411-413.]Search in Google Scholar
[David, M., Little, R., Samuhel, M., and Triest, R. (1983). Nonrandom Nonresponse Models Based on the Propensity to Respond. Proceedings of the Business and Economic Statistics Section of the American Statistical Association, 168-173.]Search in Google Scholar
[David, M., Little, R.J.A., Samuhel, M., and Triest, R. (1986). Alternative Methods for CPS Income Imputation. Journal of the American Statistical Association, 81, 29-41.10.1080/01621459.1986.10478235]Search in Google Scholar
[De Leeuw, E. and De Heer, W. (2002). Trends in Household Survey Nonresponse: A Longitudinal and International Comparison. Survey Nonresponse, R.M. Groves, D.A.]Search in Google Scholar
[Dillman, J.L. Eltinge, and R.J.A. Little (eds). New York: Wiley, 41-54.]Search in Google Scholar
[Deming, W. (1953). On a Probability Mechanism to Attain an Economic Balance Between Resultant Error of Response and the Bias of Nonresponse. Journal of the American Statistical Association, 48, 743-772.10.1080/01621459.1953.10501197]Search in Google Scholar
[Deville, J.C. and Särndal, C.-E. (1992). Calibration Estimators in Survey Sampling. Journal of the American Statistical Association, 87, 376-382.10.1080/01621459.1992.10475217]Search in Google Scholar
[Dillman, D. (1978). Mail and Telephone Surveys: The Total Design Method. New York: Wiley.]Search in Google Scholar
[Dillman, D., Smyth, J., and Christian, L. (2009). Internet, Mail, and Mixed-Mode Surveys: The Tailored Design Method, (3rd edition). New York: Wiley.]Search in Google Scholar
[Dunkelburg, W. and Day, G. (1973). Nonresponse Bias and Callbacks in Sample Surveys. Journal of Marketing Research, 10, 160-168.10.1177/002224377301000206]Search in Google Scholar
[Ferber, R. (1949). The Problem of Bias in Mail Returns: A Solution. Public Opinion Quarterly, 12, 669-676.10.1086/266009]Search in Google Scholar
[Feskins, R., Hoop, J., Lensvelt-Mulders, G., and Schmeets, H. (2011). Collecting Data Among Ethnic Minorities in an International Perspective. Field Methods, 18, 284-304.10.1177/1525822X06288756]Search in Google Scholar
[Fuller, W.A., Loughin, M.M., and Baker, H.D. (1994). Regression Weighting for the 1987-88 National Food Consumption Survey. Survey Methodology, 20, 75-85.]Search in Google Scholar
[Goyder, J. (1987). The Silent Minority: Nonrespondents on Sample Surveys. Boulder, CO: Westview Press.]Search in Google Scholar
[Greenlees, J., Reece, W., and Zieschang, K. (1982). Imputation of Missing Values When the Probability of Response Depends on the Variable Being Imputed. Journal of the American Statistical Association, 77, 251-261.10.1080/01621459.1982.10477793]Search in Google Scholar
[Groves, R.M. (2006). Nonresponse Rates and Nonresponse Bias in Household Surveys.10.1093/poq/nfl033]Search in Google Scholar
[Groves, R.M. and Couper, M.P. (1998). Nonresponse in Household Interview Surveys. New York: Wiley.10.1002/9781118490082]Search in Google Scholar
[Groves, R.M., Couper, M., Presser, S., Singer, E., Tourangeau, R., Acosta, G.P., and Nelson, L. (2006). Experiments in Producing Nonresponse Bias. Public Opinion Quarterly, 70, 720-736.10.1093/poq/nfl036]Search in Google Scholar
[Groves, R., Dillman, D., Eltinge, J., and Little, R. (2002). Survey Nonresponse. New York: Wiley, 41-54.]Search in Google Scholar
[Groves, R.M. and Heeringa, S.G. (2006). Responsive Design for Household Surveys: Tools for Actively Controlling Survey Errors and Costs. Journal of the Royal Statistical Society, Series A, 169, 439-457. 10.1111/j.1467-985X.2006.00423.x]Search in Google Scholar
[Hansen, M.H. and Hurwitz, W.N. (1946). The Problem of Non-Response in Sample Surveys. Journal of the American Statistical Association, 41, 517-529.10.1080/01621459.1946.1050189420279350]Search in Google Scholar
[Haring, R., Alte, D., Völzkea, H., Sauer, S., Wallaschofski, H., John, U., and Schmidt, C. (2009). Extended Recruitment Efforts Minimize Attrition but not Necessarily Bias. Journal of Clinical Epidemiology, 62, 252-260.10.1016/j.jclinepi.2008.06.01018834716]Search in Google Scholar
[Hartley, H.O. (1946). Discussion of “A Review of Recent Statistical Developments in Sampling and Sample surveys.”. Journal of the Royal Statistical Society, 109, 37-38.]Search in Google Scholar
[Heckman, J. (1979). Sample Selection Bias as a Specification Error. Econometrica, 47, 153-162.10.2307/1912352]Search in Google Scholar
[Holt, D. and Smith, T.M.F. (1979). Post-Stratification. Journal of the Royal Statistical Society, Series A, 142, 33-46.10.2307/2344652]Search in Google Scholar
[Ingen, E., Stoop, I., and Breedveld, K. (2009). Nonresponse in the Dutch Time Use Survey: Strategies for Response Enhancement and Bias Reduction. Field Methods, 21, 69-90.10.1177/1525822X08323099]Search in Google Scholar
[Kalton, G. (1983). Compensating for Missing Survey Data. Ann Arbor: University of Michigan Press.]Search in Google Scholar
[Kalton, G. and Flores-Cervantes, I. (2003). Weighting Methods. Journal of Official Statistics, 18, 81-97.]Search in Google Scholar
[Kalton, G. and Kasprzyk, D. (1986). The Treatment of Missing Survey Data. Survey Methodology, 12, 1-16.]Search in Google Scholar
[Keeter, S., Miller, C., Kohut, A., Groves, R.M., and Presser, S. (2000). Consequences of Reducing Nonresponse in a Large National Telephone Survey. Public Opinion Quarterly, 64, 125-148.10.1086/31775910984330]Search in Google Scholar
[Kreuter, F.,Olson,K.,Wagner, J., Yan,T.,Ezzati-Rice, T.M.,Casas-Cordero, C., Lemay,M., Peytchev, A., Groves, R.M., and Raghunathan, T.E. (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, 173, 389-407.10.1111/j.1467-985X.2009.00621.x]Search in Google Scholar
[Lin, I.-F. and Schaeffer, N.C. (1995). Using Survey Participants to Estimate the Impact of Nonparticipation. Public Opinion Quarterly, 59, 236-258.10.1086/269471]Search in Google Scholar
[Little, R.J.A. (1986). Survey Nonresponse Adjustments for Estimates of Means. International Statistical Review, 54, 139-157.10.2307/1403140]Search in Google Scholar
[Little, R.J.A. (1993). Pattern-Mixture Models for Multivariate Incomplete Data. Journal of the American Statistical Association, 88, 125-134.]Search in Google Scholar
[Little, R.J.A. and Rubin, D.B. (2002). Statistical Analysis With Missing data, (2nd edition). New York: Wiley.10.1002/9781119013563]Search in Google Scholar
[Lumley, T., Shaw, P., and Dai, J. (2011). Connections Between Survey Calibration Estimators and Semiparametric Models for Incomplete Data. International Statistical Review, 79, 200-220.10.1111/j.1751-5823.2011.00138.x369988923833390]Search in Google Scholar
[Lundstro¨m, S. and Särndal, C.-E. (1999). Calibration as a Standard Method for Treatment of Nonresponse. Journal of Official Statistics, 15, 305-327.]Search in Google Scholar
[Madow, W.G., Nisselson, H., and Olkin, I. (1983). Incomplete Data in Sample Surveys, Vol. 1. New York: Academic Press.]Search in Google Scholar
[Madow, W.G. and Olkin, I. (1983). Incomplete Data in Sample Surveys, Vol. 3. New York: Academic Press. Madow, W.G., Olkin, I., and Rubin, D.B. (1983). Incomplete Data in Sample Surveys, Vol. 2. New York: Academic Press.]Search in Google Scholar
[Merkle, D., Edelman, M., Dykeman, K., and Brogan, C. (1998). An Experimental Study of Ways to Increase Exit Poll Response Rates and Reduce Survey Error. Paper presented at the Annual Conference of the American Association for Public Opinion Research, St. Louis, MO.]Search in Google Scholar
[Micklewright, J., Schnepf, S., and Skinner, C. (2012). Non-Response Biases in Surveys of Schoolchildren: The Case of the English Programme for International Student Assessment (PISA) samples. Journal of the Royal Statistical Society, Series A, 175, 915-938.10.1111/j.1467-985X.2012.01036.x]Search in Google Scholar
[Mohadjer, L., Berlin, M., Rieger, S., Waksberg, J., Rock, D., Yamamoto, K., Kirsch, I., and Kolstad, A. (1997). The Role of Incentives in Literacy Survey Research. Adult Basic Skills: Innovations in Measurement and Policy Analysis, A. Tuijnman, I. Kirsch, and D. Wagner (eds). Creskill, NJ: Hampton Press.]Search in Google Scholar
[Molenberghs, G., Beunckens, C., Sotto, C., and Kenward, M.G. (2008). Every Missingness not at Random Model has a Missingness at Random Counterpart With Equal Fit. Journal of the Royal Statistical Society: Series B, 70, 371-388.10.1111/j.1467-9868.2007.00640.x]Search in Google Scholar
[Oh, H.L. and Scheuren, F.J. (1983). Weighting Adjustments for Unit Nonresponse. Incomplete Data in Sample Surveys, W.G. Madow, I. Olkin, and D.B. Rubin (eds). Vol. 2. New York: Academic Press, 143-184.]Search in Google Scholar
[Olsen, K. and Groves, R.M. (2012). An Examination of Within-Person Variation in Response Propensity over the Data Collection Field Period. Journal of Official Statistics, 28, 29-51.]Search in Google Scholar
[Peytcheva, E. and Groves, R.M. (2009). Using Variation in Response Rates of Demographic Subgroups as Evidence of Nonresponse Bias in Survey Estimates. Journal of Official Statistics, 25, 193-201.]Search in Google Scholar
[Phipps, P. and Toth, D. (2012). Analyzing Establishment Nonresponse Using an Interpretable Regression Tree Model with Linked Administrative Data. Annals of Applied Statistics, 6, 772-794.10.1214/11-AOAS521]Search in Google Scholar
[Politz, A. and Simmons, W. (1949). An Attempt to Get “Not at Homes” Into the Sample Without Callbacks. Journal of the American Statistical Association, 44, 9-31.]Search in Google Scholar
[Rosenbaum, P.R. and Rubin, D.B. (1983). The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika, 70, 41-55.10.1093/biomet/70.1.41]Search in Google Scholar
[Rubin, D.B. (1976). Inference and Missing Data (with discussion). Biometrika, 63, 581-592.10.1093/biomet/63.3.581]Search in Google Scholar
[Särndal, C.-E. (2011a). Morris Hansen Lecture: Dealing With Survey Nonresponse in Data Collection, in Estimation. Journal of Official Statistics, 27, 1-21.]Search in Google Scholar
[Särndal, C.-E. (2011b). Three Factors to Signal Non-Response Bias with Applications to Categorical Auxiliary Variables. International Statistical Review, 79, 233-254.10.1111/j.1751-5823.2011.00142.x]Search in Google Scholar
[Särndal, C.-E. and Lundstro¨m, S. (2005). Estimation in Surveys with Nonresponse.Chichester, UK: Wiley.10.1002/0470011351]Search in Google Scholar
[Särndal, C.-E. and Lundstro¨m, S. (2008). Assessing Auxiliary Vectors for Control of Nonresponse Bias in the Calibration Estimator. Journal of Official Statistics, 4, 251-260. ]Search in Google Scholar
[Särndal, C.-E. and Lundstro¨m, S. (2010). Design for Estimation: Identifying Auxiliary vectors to reduce nonresponse bias. Survey Methodology, 36, 131-144.]Search in Google Scholar
[Särndal, C.-E., Swensson, B., and Wretman, J. (1992). Model Assisted Survey Sampling. New York: Springer-Verlag.10.1007/978-1-4612-4378-6]Search in Google Scholar
[Schmeets, H. (2010). Increasing Response Rates and the Consequences in the Dutch Parliamentary Election Study 2006. Field Methods, 22, 391-412.10.1177/1525822X10381031]Search in Google Scholar
[Schouten, B. (2007). A Selection Strategy for Weighting Variables Under a Not-Missingat- Random Assumption. Journal of Official Statistics, 23, 51-68.]Search in Google Scholar
[Schouten, B., Calinescu, M., and Luiten, A. (2011a). Optimizing Quality of Response Through Adaptive Survey Designs. The Hague: Statistics Netherlands, Available at: http://www.cbs.nl/NR/rdonlyres/2D62BF4A-6783-4AC4-8E4512EF20C6675C/0/2011x1018.pdf. (Accessed May 24, 2013).]Search in Google Scholar
[Schouten, B., Cobben, F., and Bethlehem, J. (2009). Measures for the Representativeness of Survey Response. Survey Methodology, 35, 101-113.]Search in Google Scholar
[Schouten, B., Schlomo, N., and Skinner, C. (2011b). Indicators for Monitoring and Improving Representativeness of Response. Journal of Official Statistics, 27, 231-253.]Search in Google Scholar
[Singer, E. (2002). Use of Incentives to Reduce Nonresponse in Household Surveys.]Search in Google Scholar
[Survey Nonresponse, R. Groves, D. Dillman, J. Eltinge, and R. Little (eds). New York: Wiley, 163-177.]Search in Google Scholar
[Singer, E. and Ye, C. (2013). The Use and Effects of Incentives in Surveys. The ANNALS of the American Academy of Political and Social Science, 645, 112-141.10.1177/0002716212458082]Search in Google Scholar
[Skinner, C.J. and D’Arrigo, J. (2011). Inverse Probability Weighting for Clustered Nonresponse. Biometrika, 98, 953-966.10.1093/biomet/asr058]Search in Google Scholar
[Smith, T.W. (1995). Trends in Non-Response Rates. International Journal of Public Opinion Research, 7, 157-171.10.1093/ijpor/7.2.157]Search in Google Scholar
[Steeh, C., Kirgis, N., Cannon, B., and DeWitt, J. (2001). Are They Really as Bad as They Seem? Nonresponse Rates at the End of the Twentieth Century. Journal of Official Statistics, 17, 227-247.]Search in Google Scholar
[Steele, F. and Durrant, G.B. (2011). Alternative Approaches to Multilevel Modelling of Survey Non-Contact and Refusal. International Statistical Review, 79, 70-91.10.1111/j.1751-5823.2011.00133.x]Search in Google Scholar
[Stoop, I.A.L. (2005). The Hunt for the Last Respondent: Nonresponse in Sample Surveys. The Hague: Social and Cultural Planning Office.]Search in Google Scholar
[Stoop, I., Billiet, J., Koch, A., and Fitzgerald, R. (2010). Improving Survey Response: Lessons Learned from the European Social Survey. Chichester: Wiley.10.1002/9780470688335]Search in Google Scholar
[Synodinos, N.E. and Yamada, S. (2000). Response Rate Trends in Japanese Surveys. International Journal of Public Opinion Research, 12, 48-72.10.1093/ijpor/12.1.48]Search in Google Scholar
[Tanur, J. (1999). Looking Backwards and Forwards at the CASM Movement. Cognition and Survey Research, M. Sirken, D. Hermann, S. Schechter, N. Schwarz, J. Tanur, and R. Tourangeau (eds). New York: Wiley, 13-20.]Search in Google Scholar
[Thomsen, I. (1973). A Note on the Efficiency of Weighting Subclass Means to Reduce the Effects of Nonresponse When Analyzing Survey Data. Statistisk Tidskrift, 11, 278-285.]Search in Google Scholar
[Tourangeau, R., Rips, L.J., and Rasinski, K. (2000). The Psychology of Survey Response. New York: Cambridge University Press. Wagner, J. (2010). The Fraction of Missing Information as a Tool for Monitoring the Quality of Survey Data. Public Opinion Quarterly, 74, 223-243.]Search in Google Scholar
[Wetzels, W., Schmeets, H., Van den Brakel, J., and Feskens, R. (2008). Impact of Prepaid Incentives in Face-to-Face Surveys: A Large-Scale Experiment With Postage Stamps. International Journal of Public Opinion Research, 20, 507-516.10.1093/ijpor/edn050]Search in Google Scholar
[Yates, F. (1946). A Review of Recent Statistical Developments in Sampling and Sample Surveys. Journal of the Royal Statistical Society, 109, 12-43. 10.2307/2981390]Search in Google Scholar