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Exploring nonresponse bias in a health survey using neighborhood characteristics

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  • Lee, S.
  • Brown, E.R.
  • Grant, D.
  • Belin, T.R.
  • Brick, J.M.

Abstract

Objectives. We examined potential nonresponse bias ina large-scale, population-based, random-digit-dialed telephone survey in California and its association with the response rate. Methods. We used California Health Interview Survey (CHIS) data and US Census data and linked the two data sets at the census tract level. We compared a broad range of neighborhood characteristics of respondents and nonrespondents to CHIS. We projected individual-level nonresponse bias using the neighborhood characteristics. Results. We found little to no substantial difference in neighborhood characteristics between respondents and nonrespondents. The response propensity of the CHIS sample was similarly distributed across these characteristics. The projected nonresponse bias appeared very small. Conclusions. The response rate in CHIS did not result in significant nonresponse bias and did not substantially affect the level of data representativeness, and it is not valid to focus on response rates alone in determining the quality of survey data.

Suggested Citation

  • Lee, S. & Brown, E.R. & Grant, D. & Belin, T.R. & Brick, J.M., 2009. "Exploring nonresponse bias in a health survey using neighborhood characteristics," American Journal of Public Health, American Public Health Association, vol. 99(10), pages 1811-1817.
  • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2008.154161_1
    DOI: 10.2105/AJPH.2008.154161
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    Cited by:

    1. Dean, Lorraine & Subramanian, S.V. & Williams, David R. & Armstrong, Katrina & Charles, Camille Zubrinsky & Kawachi, Ichiro, 2014. "The role of social capital in African–American women's use of mammography," Social Science & Medicine, Elsevier, vol. 104(C), pages 148-156.
    2. R. S. Oropesa & Nancy S. Landale & Marianne M. Hillemeier, 2016. "Legal Status and Health Care: Mexican-Origin Children in California, 2001–2014," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 35(5), pages 651-684, October.
    3. Edwards Brad, 2017. "Discussion," Journal of Official Statistics, Sciendo, vol. 33(4), pages 887-890, December.
    4. Jessica Saunders & Layla Parast & Susan H Babey & Jeremy V Miles, 2017. "Exploring the differences between pet and non-pet owners: Implications for human-animal interaction research and policy," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-15, June.
    5. Shaoqing Gong & Liang Wang & Zhongliang Zhou & Kesheng Wang & Arsham Alamian, 2022. "Income Disparities in Obesity Trends among U.S. Adults: An Analysis of the 2011–2014 California Health Interview Survey," IJERPH, MDPI, vol. 19(12), pages 1-9, June.
    6. Oropesa, R.S. & Landale, Nancy S. & Hillemeier, Marianne M., 2015. "Family legal status and health: Measurement dilemmas in studies of Mexican-origin children," Social Science & Medicine, Elsevier, vol. 138(C), pages 57-67.
    7. Michael R. Greenberg & Marc D. Weiner, 2014. "Keeping Surveys Valid, Reliable, and Useful: A Tutorial," Risk Analysis, John Wiley & Sons, vol. 34(8), pages 1362-1375, August.

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