Summary
One of the most salient data problems empirical researchers face is the lack of informative responses in survey data. This contribution briefly surveys the literature on item nonresponse behavior and its determinants before it describes four approaches to address item nonresponse problems: Casewise deletion of observations, weighting, imputation, and model-based procedures. We describe the basic approaches, their strengths and weaknesses and illustrate some of their effects using a simulation study. The paper concludes with some recommendations for the applied researcher.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Barnard, J., Rubin, D. B. (1999). Small-sample degrees of freedom with multiple imputation. Biometrika 86 948–955.
Dempster, A. P., Laird, N. M., Rubin, D. B. (1977). Maximum likelihood estimation from incomplete data via the EM algorithm (with discussion). Journal of the Royal Statistical Society, Series B 39 1–38.
Deville, J. C., Särndal, C. E. (1992). Calibration estimators in survey sampling. Journal of the American Statistical Association 87 376–382.
Deville, J. C., Särndal, C. E., Sautory, O. (1993). Generalized raking procedures in survey sampling. Journal of the American Statistical Association 88 1013–1020.
Dillman, D. A., Eltinge, J. L., Groves, R. M., Little, R. J. A. (2002). Survey nonresponse in design, data collection, and analysis. In Survey Nonresponse (R. M. Groves, D. A. Dillman, J. L. Eltinge, R. J. A. Little, eds.), 3–26. Wiley, New York.
Esser, H. (1984). Determinanten des Interviewer-und Befragtenverhaltens: Probleme der theoretischen Erklärung und empirischen Untersuchung von Interviewerfeffekten. In Allgemeine Bevölkerungsumfrage der Sozialwissenschaften (K. Mayer, P. Schmidt, eds.), 26–71. Campus, Frankfurt.
Frick, J. R., Grabka, M. M. (2003). Missing income data in the German SOEP: Incidence, imputation and its impact on the income distribution. DIW Discussion Papers 376, DIW Berlin.
Gelman, A., Carlin, J. B. (2002). Poststratification and weighting adjustment. In Survey Nonresponse (R. M. Groves, D. A. Dillman, J. L. Eltinge, R. J. A. Little, eds.), 289–302. Wiley, New York.
Glynn, R., Laird, N. M., Rubin, D. B. (1986). Selection modeling versus mixture modeling with nonignorable nonresponse. In Drawing Inferences from Self-Selected Samples (H. Wainer, ed.), 119–146, Springer, New York.
Groves, R. M., Dillman, D. A., Eltinge, J. L., Little, R. J. A. (2002). Survey Nonresponse. Wiley, New York.
Hartley, H. O., Hocking, R. R. (1971). The analysis of incomplete data. Biometrics 27 783–808.
Heckman, J. J. (1976). The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models. Annals of Economic and Social Measurement 5 475–492.
Horton, N. J., Lipsitz, S. R. (2001). Multiple imputation in practice: Comparison of software packages for regression models with missing variables. American Statistician 55 244–254.
Lee, H., Rancourt, E., Särndal, C. E. (2002). Variance estimation from survey data under single imputation. In Survey Nonresponse (R. M. Groves, D. A. Dillman, J. L. Eltinge, R. J. A. Little, eds.), 315–328. Wiley, New York.
Little, R. J. A. (1993). Pattern-mixture models for multivariate incomplete data. Journal of the American Statistical Association 88 125–134.
Little, R. J. A., Rubin D. B. (1987, 2002). Statistical analysis with missing data. 1 and 2. ed., Wiley, Hoboken, New Jersey.
Madow, W. G., Olkin, I., Rubin, D. B. (1983). Incomplete Data in Sample Surveys. Academic Press, New York.
McLachlan, G. J., Krishnan, T. (1997). The EM Algorithm and Extensions. Wiley, New York.
Münnich, R., Rässler, S. (2005). PRIMA: A new multiple imputation procedure for binary variables. Journal of Official Statistics (to appear).
Oh, J. L., Scheuren, F. (1983). Weighting adjustment for unit nonresponse. In Incomplete Data in Sample Surveys 2 (W. G. Madow, I. Olkin, D. B. Rubin, eds.), 143–184. Academic Press, New York.
Raghunathan, T. E., Rubin, D. B. (1998). Roles for Bayesian Techniques in Survey Sampling. Proceedings of the Silver Jubilee Meeting of the Statistical Society of Canada 51–55.
Rässler, S., Rubin, D. B., Schenker, N. (2003). Imputation. In Encyclopedia of Social Science Research Methods (A. Bryman, M. Lewis-Beck, T. F. Liao, eds.), 477–482. Sage, Thousand Oaks.
Rässler, S., Schnell, R. (2004). Multiple imputation for unit nonresponse versus weighting including a comparison with a nonresponse follow-up study. Diskussionspapier der Lehrstühle für Statistik 65/2004, Nürnberg.
Riphahn, R. T., Serfling, O. (2002). Item non-response on income and wealth questions. IZA Discussion Paper No. 573, IZA Bonn.
Riphahn, R. T., Serfling, O. (2005). Item non-response on income and wealth questions. Empirical Economics (to appear).
Rubin, D. B. (1972). A non-iterative algorithm for least squares estimation of missing values in any analysis of variance design. The Journal of the Royal Statistical Society, Series C 21 136–141.
Rubin, D. B. (1974). Characterizing the estimation of parameters in incompletedata problems. Journal of the American Statistical Association 69 467–474.
Rubin, D. B. (1976). Inference and missing data. Biometrika 63 581–592.
Rubin, D. B. (1978). Multiple imputation in sample surveys—a phenomenological Bayesian approach to nonresponse. Proceedings of the Survey Research Methods Sections of the American Statistical Association 20–40.
Rubin, D. B. (1987, 2004). Multiple Imputation for Nonresponse in Surveys. 1 and 2. ed., Wiley, Hoboken, New Jersey.
Rubin, D. B. (1996). Multiple imputation after 18+years (with discussion). Journal of the American Statistical Association 91 473–489.
Rubin, D. B., Schenker, N. (1986). Multiple imputation for interval estimation from simple random samples with ignorable nonresponse. Joural of the American Statistical Association 81 366–374.
Schafer, J. L. (1997). Analysis of Incomplete Multivariate Data. Chapman and Hall, London.
Schräpler, J. P. (2004). Respondent behavior in panel studies. A case study for income nonresponse by means of the Germany Socio-Economic Panel (SOEP). Sociological Methods and Research 33 118–156.
Sudman, S., Bradburn, N. M., Schwarz, N. (1996). Thinking about Answers. The Application of Cognitive Processes to Survey Methodology. Jossey Bass Publishers, San Francisco.
Author information
Authors and Affiliations
Additional information
We are grateful to an anonymous referee who provided helpful comments. Also we like to thank Donald B. Rubin for helpful comments and always motivating discussions as well as Ralf Münnich for inspiring discussions about raking procedures.
Rights and permissions
About this article
Cite this article
Rässler, S., Riphahn, R.T. Survey item nonresponse and its treatment. Allgemeines Statistisches Arch 90, 217–232 (2006). https://doi.org/10.1007/s10182-006-0231-3
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/s10182-006-0231-3