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Cited by 2,420Survey Methodology and NonresponseSurvey Sampling and Estimation TechniquesCensus and Population Estimation

The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.

Nonresponse Rates and Nonresponse Bias in Household Surveys

Groves, Robert M.·2006·Public Opinion Quarterly
DOI 10.1093/poq/nfl033
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Abstract

Many surveys of the U.S. household population are experiencing higher refusal rates. Nonresponse can, but need not, induce nonresponse bias in survey estimates. Recent empirical findings illustrate cases when the linkage between nonresponse rates and nonresponse biases is absent. Despite this, professional standards continue to urge high response rates. Statistical expressions of nonresponse bias can be translated into causal models to guide hypotheses about when nonresponse causes bias. Alternative designs to measure nonresponse bias exist, providing different but incomplete information about the nature of the bias. A synthesis of research studies estimating nonresponse bias shows the bias often present. A logical question at this moment in history is what advantage probability sample surveys have if they suffer from high nonresponse rates. Since postsurvey adjustment for nonresponse requires auxiliary variables, the answer depends on the nature of the design and the quality of the auxiliary variables.

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Citations

Cites

Research works printed but not linked: 15

  1. AAPOR, 2006, Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Survey
  2. Bogen, 1996, The Effect of Questionnaire Length on Response Rates: A Review of the Literature, 1020
  3. Botman, 1992, Survey Design Features Correlates of Nonresponse, 309
  4. Brick, 2003, No. 8: 2002 NSAF Response Rates
  5. Brick, 2003, Dealing with Movers in a Longitudinal Study of Children, 2
  6. Brunner, 1969, The Effect of Prior Notification on the Refusal Rate in Fixed Address Surveys, Journal of Advertising, 9, 42
  7. Cannell, 1963, A Study of the Reporting Visits to Doctors in the National Health Survey
  8. Deville, 1991, A Theory of Quota Surveys, Survey Methodology, 17, 163
  9. Ekholm, 1991, Weighting via Response Modeling in the Finnish Household Budget Survey, Journal of Official Statistics, 7, 1325
  10. Groves, 2004, Survey Methodology
  11. Luppes, 2000, A Content Analysis of Advance Letters from Expenditure Surveys of Seven Countries, Journal of Official Statistics, 11, 461
  12. Merkle, 2002, Nonresponse in Exit Polls: A Comprehensive Analysis, 243
  13. Nealon, 1983, The Effects of Male vs. Female Telephone Interviewers, 139
  14. Office of Management and Budget (OMB), 2006, Questions and Answers When Designing Surveys for Information Collections
  15. Stephan, 1958, Sampling Opinions

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Metadata

Authors
Groves, R. M.
Affiliations
U.S. National Science Foundation (US)
Corresponding author
Groves, Robert M.
Venue
Public Opinion Quarterly
Publisher
Oxford University Press (OUP)
Published
2006
Volume
70
Issue
5
Pages
646-675
ISSN
  • 0033-362X (ISSN-L)
  • 1537-5331
DOI
10.1093/poq/nfl033
OpenAlex
W2116971494
Cited by
2,420
References
80
Citations by year
2026: 90 · 2025: 78 · 2024: 87 · 2023: 90 · 2022: 103 · 2021: 129 · 2020: 152 · 2019: 133 · 2018: 152 · 2017: 161 · 2016: 155 · 2015: 176 · 2014: 170 · 2013: 152 · 2012: 163
FWCI
193.26
Type
journal article
Language
en
Open access
closed
Locations
Public Opinion Quarterly (publishedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
  • Physical Sciences › Mathematics › Statistics and Probability › Survey Sampling and Estimation Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Census and Population Estimation
Keywords
nonresponse bias, nonresponse rates, household surveys, response rate, auxiliary variables

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