Abstract
Although item nonresponse can never be totally prevented, it can be considerably reduced, and thereby provide the researcher with not only more useable data, but also with helpful auxiliary information for a better imputation and adjustment. To achieve this an optimal data collection design is necessary. The optimization of the questionnaire and survey design are the main tools a researcher has to reduce the number of missing data in any such survey. In this contribution a concise typology of missing data patterns and their sources of origin are presented. Based on this typology, the mechanisms responsible for missing data are identified, followed by a discussion on how item nonresponse can be prevented.
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Arbuckle, J. (1996). Full information estimation in the presence of missing data. In: G. A. Marcoulides & R. E. Schumacker (eds), Advanced Structural Equation Modeling. Mahwah, NY: Erlbaum.
Billiet, J.& Loosveldt, G. (1988). Improvement of the quality of responses to factual survey questions by interviewer training. Public Opinion Quarterly 52: 190-211.
Campanelli, P. (1997). Testing survey questions: new directions in cognitive interviewing. BMS 55: 5-17 (special issue on the cognitive interview).
Carton, A. (1999). Selectie, Training en Evaluatie van Interviewers binnen een Interviewernetwerk [In Dutch: An Interviewer Network: Constructing a Procedure to Evaluate Interviewers]. Leuven: Garant.
Colsher, P. L. & Wallace, R. B. (1989). Data quality and age: health and psychobehavioral correlates of item nonresponse and inconsistent responses. Journal of Gerontology 44: 45-52.
Conan Doyle, Sir Arthur. (1981). The Copper Beeches: The Adventures of Sherlock Holmes. London: Penguin Books, p. 268.
Couper, M. P., Hansen, S. E. & Sadovsky, S. A. (1997). Evaluating interviewer use of CAPI technology. In: L. Lyberg et al. (eds), Survey Measurement and Process Quality. New York: Wiley, pp. 267-285.
De Leeuw, E. D. (1992). Data Quality in Mail, Telephone, and Face to Face Surveys. Amsterdam: TT publikaties.
De Leeuw, E. D. & Collins, M. (1997). Data collection method and survey quality: an overview. In: L. Lyberg et al. (eds), Survey Measurement and Process Quality. New York: Wiley, pp. 199-220.
De Leeuw, E. D., Hox, J. J. & Snijkers, G. (1998). The effect of computer-assisted interviewing on data quality. In: B. Blyth (ed.), Market Research and Information Technology. Application and Innovation. Esomar Monograph 6. Amsterdam: Esomar, pp. 173-198.
De Leeuw, E. D., Hox, J., Kef, S. & Van Hattum, M. (1997). Overcoming the problems of special interviews on sensitive topics: computer assisted self-interviewing tailored for young children and adolescents. Sawtooth Software Conference Proceedings. Sequim, WA: Sawtooth.
Dillman, D. A. (1978). Mail and Telephone Surveys: The Total Design Method. New York: Wiley (a fully revised and updated version is now in press).
Dippo, C. S. (1997). Survey measurement and process improvement: concepts and integration. In: L. Lyberget al. (eds), Survey Measurement and Process Quality. New York: Wiley, pp. 457-474.
Dykema, J., Lepkowski, J. M. & Blixt, S. (1997). The effect of interviewer and respondent behavior on data quality: an analysis of interaction coding in a validation study. In: L. Lyberg et al. (eds), Survey Measurement and Process Quality. New York: Wiley, pp. 287-310.
Engel, U. & Reinecke, J. (1994). Panelanalyse: Grundlagen, Techniken, Beispiele. Berlin: Walter de Gruyter.
Fowler, F. J., Jr. (1991). Reducing interviewer related error through interviewer training, supervision and other means. In: P. Biemer et al. (eds), Measurement Errors in Surveys. New York: Wiley, pp. 259-278.
Freedman, D. S., Thornton, A. & Camburn, D. (1980). Maintaining response rates in longitudinal studies. Sociological Methods & Research 9: 87-98.
Forsyth, B. H. & Lessler, J. T. (1991). Cognitive laboratory methods: a taxonomy. In: P. Biemer et al. (eds), Measurement Errors in Surveys. New York: Wiley, pp. 393-418.
Groves, R. M. (1989). Survey Errors and Survey Costs. New York: Wiley.
Groves, R. M. & Couper, M. P. (1998). Nonresponse in Household Interview Surveys. New York: Wiley.
Hermkens, P. L. J. (1983). Oordelen over de rechtvaardigheid van inkomens [In Dutch: Judgements on the Fairness of Income]. Amsterdam: Kobra.
Herzog, A. R. & Rodgers, W. L. (1992). The use of survey methods in research on older Americans. In: R. B. Wallace & R. F. Woolson (eds). The Epidemiological Study of the Elderly. Oxford: Oxford University Press.
Hippler, H.-J., Schwarz, N. & Singer, E. (1990). Der influess von Datenschutzzusagen auf die teilnamebereitschaft an Umfragen[In German: The influence of dataprotection reassurance on the willingness to participate in a survey]. ZUMA nachrichten 27: 54-67.
Hox, J. J. (1999). A review of current software for handling missing data. Kwantitieve Methoden (in press).
Hox, J. J., Kreft, I. G. G. & Hermkens, P. L. J. (1991). The analysis of factorial surveys. Sociological Methods & Research 19: 493-510.
Huisman, M., Krol, B. & Van Sonderen, F. L. P. (1998). Handling missing data by reapproaching nonrespondents. Quality and Quantity 32: 77-91.
Huisman, M. (1999). Item Nonresponse: Occurrence, Causes, and Imputation of Missing Answers to Test Items. Leiden: DSWO Press.
Jansen, M. G. H. (1997). The rasch model for speed tests and some extensions with applications to incomplete designs. Journal of Educational and Behavioral Statistics 22: 125-140.
Jenkins, C. R. & Dillman, D. A. (1997). Towards a theory of self-administered questionnaire design. In: L. Lyberg et al. (eds), Survey Measurement and Process Quality. New York: Wiley, pp. 165-196.
Kasprzyk, D., Duncan, G. J., Kalton, G. & Singh, M. P. (1989). Panel Surveys. New York: Wiley.
Krosnick, J. A. & Fabrigar, L. R. (1997). Designing rating scales for effective measurement in surveys. In: L. Lyberg et al. (eds), Survey Measurement and Process Quality. New York: Wiley, pp. 141-164.
Lavrakas, P. (1999). Personal communication to AAPOR-net, June 11.
Leigh, J. H. & Martin, C. R. (1987). Do-not-know item nonresponse in telephone surveys: effects of question form and respondent characteristics. Journal of Marketing Research 24: 418-424.
Lessler, J. T. & Kalsbeek, W. D. (1992). Nonsampling Error in Surveys. New York: Wiley.
Little, R. J. A. & Rubin, D. B. (1987). Statistical Analysis with Missing Data. New York: Wiley.
Martin, J. et al. (1996). Task Force on Imputation, Report on Imputation. Government Statistical Services, Methodology Series, #3, UK: GSS/ONS.
Morton-Williams, J. (1993). Interviewer Approaches. Aldershot: Darthmouth Publications
McCrossan, L. (1991). A Handbook for Interviewers. London: HMSO.
Nicholls, W. L. II., Baker, R. P. & Martin, J. (1997). The effect of new data collection technologies on survey data quality. In: L. Lyberg et al. (eds). Survey Measurement and Process Quality. New York: Wiley, pp. 221-248.
Saris, W. E. (1998). Ten years of interviewing without interviewers. In: M. P. Couper et al. (eds), Computer Assisted information Collection. New York: Wiley.
Skinner, C. (1999). Developing an imputation strategy, with illustrations from a self-completion survey of local authorities. Lecture presented at the Survey Methods Centre seminar on item nonresponse in surveys. London: Royal Statistical Society, March 1999.
Strack, F. & Martin, L. (1987). Thinking judging and communicating: a process account of context effects in attitude surveys. In: H. J. Hippler et al. (eds), Social Information Processing and Survey Methodology. New York: Springer Verlag, pp. 123-148.
Sudman, S. & Bradburn, N. M. (1974). Response Effects in Surveys. Chicago: Aldine.
Schuman, H. H. & Presser, S. (1981). Questions &Answers in Attitude Surveys. New York: Academic Press.
Scherpenzeel, A. & Saris, W. (1997). The validity and reliability of survey questions: a meta-analysis of MTMM studies. Sociological Methods and Research 25: 341-383.
Schwarz, N. (1997). Questionnaire design: the rocky road from concepts to answers. In: L. Lyberg et al. (eds). Survey Measurement and Process Quality. New York: Wiley, pp. 29-45.
Snijkers, G., Akkerboom, H., Kuijpers, I, De Leeuw, E. (1996). Computer-assisted qualitative interviewing: an intermediate technology of quality assessment. Paper presented at INTERCASIC '96, San Antonio, Texas, 11-12 December 1996.
Tourangeau, R. (1984). Cognitive science and survey methods: a cognitive perspective. In: T. Jabine et al. (eds), Cognitive Aspects of Survey Methodology: Building a Bridge between Disciplines. Washington DC: National Academy Press, pp. 73-100.
Van Hattum, M. & Leeuw, E. D. (1999). A disk-by-mail survey of teachers and pupils in Dutch primary schools: logistics and data quality. Journal of Official Statistics 3(in press).
Van de Pol, F. J. R. (1989). Issues of Design and Analysis of Panels. Amsterdam: Sociometric Research Foundation.
Van der Zouwen, J., Dijkstra, W. & Smith, J. (1991). Studying respondent-interviewer interaction: the relationship between interviewer style, interviewer behavior and response behavior. In: P. Biemer et al. (eds), Measurement Errors in Surveys. New York: Wiley, pp. 419-438.
Vermunt, J. (1996). Causal log-linear modeling with latent variables and missing data. In: U. Engel & J. Reinecke (eds). Analysis of Change. Advanced Techniques in Panel Data Analysis. New York: De Gruyter.
Weisband, S. & Kiesler, S. (1996). Self Disclosure on Computer Forms: Meta-Analysis and Implications. Tucson: University of Arizona. (http://www.al.arizona.edu_weisband/chi/chi96.html)
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de Leeuw, E.D. Reducing Missing Data in Surveys: An Overview of Methods. Quality & Quantity 35, 147–160 (2001). https://doi.org/10.1023/A:1010395805406
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DOI: https://doi.org/10.1023/A:1010395805406