Noncoverage and nonresponse in an Internet survey

Social Science Research

Volumn 36, Issue 1, 2007, Pages 131-148

  Couper, Mick P ^a   Kapteyn, Arie ^b   Schonlau, Matthias ^b   Winter, Joachim ^c  

^a UNIVERSITY OF MICHIGAN   (United States)

^b RAND CORPORATION   (United States)

^c UNIVERSITY OF MUNICH   (Germany)

Author keywords

Internet survey; Nonresponse; Survey coverage; Web survey

Indexed keywords

EID: 33750941584     PISSN: 0049089X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ssresearch.2005.10.002     Document Type: Article

References (31)

1. American Association for Public Opinion Research, (2004). Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys, third ed., Lenexa, KS: AAPOR.
2. Berrens R.P., Bohara A.K., Jenkins-Smith H., Silva C., and Weimer D.L. The advent of internet surveys for political research: a comparison of telephone and Internet samples. Political Analysis 11 1 (2003) 1-22
3. Best S.J., Krueger B., Hubbard C., and Smith A. An assessment of the generalizability of internet surveys. Social Science Computer Review 19 2 (2001) 131-145
4. Couper M.P. Web surveys: a review of issues and approaches. Public Opinion Quarterly 64 4 (2000) 464-494
5. Couper M.P. The promises and perils of Web surveys. In: Westlake A., et al. (Ed). The Challenge of the Internet (2001), Association for Survey Computing, London 35-56
6. Cox D.R., and Snell E.J. The Analysis of Binary Data. second ed. (1989), Chapman and Hall, London
7. Dillman D.A., and Bowker D.K. The Web questionnaire challenge to survey methodologists. In: Reips U.-D., and Bosnjak M. (Eds). Dimensions of Internet Science (2001), Pabst Science Publishers, Lengerich, Germany 159-177
8. Fricker R.D., and Schonlau M. Advantages and disadvantages of Internet research surveys: evidence from the literature. Field Methods 14 4 (2002) 347-365
9. Hosmer D.W., and Lemeshow S. Applied Logistic Regression. second ed. (2000), Wiley, New York
10. Katz S., Ford A., Moskowitz R., Jackson B., and Jaffe M. Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. Journal of the American Medical Association 185 (1963) 914-919
11. Kehoe C.M., and Pitkow J. Surveying the territory: GVU's five WWW user surveys. The World Wide Web Journal 1 3 (1996) 77-84
12. Lawton M.P., and Brody E.M. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist 9 3 (1969) 179-186
13. Loges W.E., and Jung J.-Y. Exploring the digital divide; Internet connectedness and age. Communication Research 28 4 (2001) 536-562
14. Nagelkerke N.J.D. A note on a general definition of the coefficient of determination. Biometrika 78 (1991) 691-692
15. Nagi S.Z. Disability and Rehabilitation: Legal, Clinical, and Self-Concepts and Measurement (1969), Ohio State University Press, Columbus
16. Nagi S.Z. An epidemiology of disability among adults in the United States. The Milbank Memorial Quarterly Fund Fall (1976) 439-467
17. National Telecommunications and Information Administration (NTIA), 1999. Falling Through the Net: Defining the Digital Divide. U.S. Department of Commerce, Washington, DC.
18. National Telecommunications and Information Administration (NTIA), 2000. Falling Through the Net: Toward Digital Inclusion. U.S. Department of Commerce, Washington, DC.
19. National Telecommunications and Information Administration (NTIA), 2001. A Nation Online: How Americans Are Expanding Their Use of the Internet. U.S. Department of Commerce, Washington, DC.
20. Radloff L.S. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement 1 (1977) 385-401
21. Rice R.E., and Katz J.E. Comparing Internet and mobile phone usage: digital divides of usage, adoption, and dropouts. Telecommunications Policy 27 (2003) 597-623
22. Tourangeau R., Couper M.P., and Conrad F.G. Spacing, position, and order: interpretive heuristics for visual features of survey questions. Public Opinion Quarterly 68 3 (2004) 368-393
23. Schonlau M., Asch B.J., and Du C. Web surveys as part of a mixed-mode strategy for populations that cannot be contacted by e-mail. Social Science Computer Review 21 2 (2003) 218-222
24. Schonlau M., Zapert K., Simon L.P., Sanstad K.H., Marcus S.M., Adams J., Spranca M., Kan H.-J., Turner R., and Berry S.H. CA comparison between responses from a propensity-weighted web survey and an identical RDD survey. Social Science Computer Review 22 1 (2004) 128-138
25. Schonlau, M., van Soest, A., Kapteyn, A., Couper, M.P., Winter, J., 2004b. Attempting to Adjust for Selection Bias in Web Surveys with Propensity Scores: The Case of the Health and Retirement Survey (HRS). Paper presented at the Joint Statistical Meetings of the American Statistical Association, Toronto, August.
26. Smith T.W. An experimental comparison of knowledge networks and the GSS. International Journal of Public Opinion Research 15 2 (2003) 167-179
27. Sparrow N., and Curtice J. Measuring the attitudes of the general public via Internet polls: an evaluation. International Journal of Market Research 46 1 (2004) 23-45
28. Steffick, D.E., 2000. Documentation of Affective Functioning Measures in the Health and Retirement Study. Institute for Social Research, University of Michigan: HRS/AHEAD Documentation Report DR-005.
29. Terhanian, G., 2000. How To Produce Credible, Trustworthy Information Through Internet-Based Survey Research. Paper presented at the annual conference of the American Association for Public Opinion Research, Portland, OR, May.
30. Weir, D.R., 2004. Modes, Trends, and Content: A Comparison of the 2003 HRS Internet Survey with HRS 2002 and 2004 Core Survey Responses for Evaluative, Subjective, and Objective Content. Institute for Social Research, University of Michigan, unpublished paper.
31. Witte J.C., Amoroso L.M., and Howard P.E.N. Method and representation in Internet-based survey tools-mobility, community, and cultural identity in survey 2000. Social Science Computer Review 18 2 (2000) 179-195