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: Statistics in Society

Volumn 173, Issue 2, 2010, Pages 389-407

  Kreuter, F ^a   Olson, K ^b   Wagner, J ^c   Yan, T ^d   Ezzati Rice, T M ^e   Casas Cordero, C ^a   Lemay, M ^a   Peytchev, A ^f   Groves, R M ^c   Raghunathan, T E ^c  

^a UNIVERSITY OF MARYLAND   (United States)

^b UNIVERSITY OF NEBRASKA LINCOLN   (United States)

^c UNIVERSITY OF MICHIGAN   (United States)

^d National Opinion Research Center   (United States)

^e AGENCY FOR HEALTHCARE RESEARCH AND QUALITY   (United States)

^f RTI INTERNATIONAL   (United States)

Author keywords

Interviewer observations; Non response adjustment; Non response bias; Paradata; Response propensity weights

Indexed keywords

EID: 77950949283     PISSN: 09641998     EISSN: 1467985X     Source Type: Journal    
DOI: 10.1111/j.1467-985X.2009.00621.x     Document Type: Article

References (39)

1. Abraham K G, Maitland A, Bianchi S M. Nonresponse in the American Time Use Survey: who is missing from the data and how much does it matter? Publ. Opin. Q. 2006, 70:676-703.
2. Atrostic B, Bates N, Silberstein A. Nonresponse in U.S. government household surveys: consistent measures, recent trends, and new insights. J. Off. Statist. 2001, 17:209-226.
3. Bates N, Dahlhamer J, Singer E. Privacy concerns, too busy, or just not interested: using doorstep concerns to predict survey nonresponse. J. Off. Statist. 2008, 24:591-612.
4. Bethlehem J. Weighting nonresponse adjustments based on auxiliary information. Survey Nonresponse 2002, 275-287. Groves RDillman DEltinge JLittle R. In, eds, pp, New York, Wiley
5. Bingham C. Crash Risk among Teen Drivers: Identification and Prediction of Excess Risk 2007, Ann Arbor, University of Michigan Transportation Research Institute
6. The 2004 National Election Study data set. 2004, Center for Political Studies, University of Michigan, Ann Arbor
7. Cohen J W. Design and Methods of the Medical Expenditure Panel Survey Household Component 1997, Rockville, Agency for Health Care Policy and Research
8. Copas A J, Farewell V T. Dealing with non-ignorable non-response by using an 'enthusiasm-to-respond' variable. J. R. Statist. Soc. A 1998, 161:385-396.
9. Couper M P. Survey introductions and data quality. Publ. Opin. Q. 1997, 61:317-338.
10. Couper M P. Measuring survey quality in a CASIC environment. Proc. Surv. Res. Meth. Sect. Am. Statist. Ass. 1998, 41-49.
11. Couper M P, Singer E, Kulka R A. Participation in the 1990 decennial census-politics, privacy, pressures. Am. Polit. Q. 1998, 26:59-80.
12. Curtain R, Presser S, Singer E. Changes in telephone survey nonresponse over the past quarter century. Publ. Opin. Q. 2005, 69:87-98.
13. De Leeuw E, DeHeer W. Trends in household survey nonresponse: a longitudinal and international comparison. Survey Nonresponse 2002, 41-54. Groves R, Dillman DEltinge JLittle R. In, eds, pp, New York, Wiley
14. Dillman D, Eltinge J, Groves R, Little R. Survey nonresponse in design, data collection and analysis. Survey Nonresponse 2002, 3-26. Groves R, Dillman D, Eltinge J, Little R. In, eds, pp, New York, Wiley
15. Ezzati-Rice T M, Rohde F, Greenblatt J. Sample Design of the Medical Expenditure Panel Survey, 1998-2007 2008, Rockville, Agency for Healthcare Research and Quality
16. Feskens R, Hox J, Lensvelt-Mulders G, Schmeets H. Nonresponse among ethnic minorities: a multivariate analysis. J. Off. Statist. 2007, 23:387-408.
17. Groves R M. Nonresponse rates and non-response bias in household surveys. Publ. Opin. Q. 2006, 70:646-675.
18. Groves R, Couper M. Nonresponse in Household Interview Surveys 1998, New York, Wiley
19. Groves R, McGonagle K. A theory-guided interviewer training protocol regarding survey participation. J. Off. Statist. 2001, 17:249-266.
20. Groves R, Peytcheva E. The impact of non-response rates on non-response bias: a meta-analysis. Publ. Opin. Q. 2008, 72:167-189.
21. Groves B, Wagner J, Peytcheva E. Use of interviewer judgments about attributes of selected respondents in post-survey adjustment for unit nonresponse: an illustration with the National Survey of Family Growth. Proc. Surv. Res. Meth. Sect. Am. Statist. Ass. 2007, 3428-3431.
22. Janson H. Influences on participation rate in a national Norwegian child development screening questionnaire study. Acta Paed. 2003, 92:91-96.
23. Johnson T, Cho Y, Campbell R, Holbrook A. Using community-level correlates to evaluate nonresponse effects in a telephone survey. Publ. Opin. Q. 2006, 70:704-719.
24. Kalton G, Flores-Cervantes I. Weighting methods. J. Off. Statist. 2003, 19:81-97.
25. Kish L. Survey Sampling 1965, New York, Wiley
26. Kreuter F, Lemay M, Casas-Cordero C. Using proxy measures of survey outcomes in post-survey adjustments: examples from the European Social Survey (ESS). Proc. Surv. Res. Meth. Sect. Am. Statist. Ass. 2007, 3142-3149.
27. Lepkowski J, Mosher W, Davis K, Groves R, van Hoewyk J, Willem J. National Survey of Family Growth, Cycle 6: sample design, weighting, imputation, and variance estimation. Vitl Hlth Statist. Ser. 2006, 1-82. 2, no. 142
28. Little R. Survey nonresponse adjustments for estimates of means. Int. Statist. Rev. 1986, 54:139-157.
29. Little R, Rubin D. Statistical Analysis with Missing Data 2002, Hoboken, Wiley
30. Little R J, Vartivarian S. On weighting the rates in non-response weights. Statist. Med. 2003, 22:1589-1599.
31. Little R, Vartivarian S. Does weighting for nonresponse increase the variance of survey means? Surv. Methdol. 2005, 31:161-168.
32. Lynn P. PEDAKSI: methodology for collecting data about survey non-respondents. Qual. Quant. 2003, 37:239-261.
33. Nicoletti C, Peracchi F. Survey response and survey characteristics: microlevel evidence from the European Community Household Panel. J. R. Statist. Soc. A 2005, 168:763-781.
34. Peytchev A, Olson K. Using interviewer observations to improve nonresponse adjustments: NES 2004. Proc. Surv. Res. Meth. Sect. Am. Statist. Ass. 2007, 3364-3371.
35. Rogers A, Murtaugh M A, Edwards S, Slattery M L. Contacting controls: are we working harder for similar response rates and does it make a difference? Am. J. Epidem. 2004, 160:85-90.
36. Rosenbaum P, Rubin D. The central role of the propensity score in observational studies for causal effects. Biometrika 1983, 70:41-55.
37. Schnell R. Nonresponse in Bevölkerungsumfragen 1997, Opladen, Leske and Budrich
38. Wun L-M, Ezzati-Rice T. Assessment of the impact of health variables on nonresponse adjustment in the medical expenditure panel survey (MEPS). Proc. Surv. Res. Meth. Sect. Am. Statist. Ass. 2007, 2857-2864.
39. Yan T, Raghunathan T. Using proxy measures of the survey variables in post-survey adjustment in a transportation survey. Proc. Surv. Res. Meth. Sect. Am. Statist. Ass. 2007, 3349-3355.