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Comparing different methods to detect and correct nonresponse bias in postal questionnaire studies.

Martin Tickle1, Keith M Milsom, Anthony S Blinkhorn

  • 1University of Manchester Dental School, Higher Cambridge Street, Manchester, UK, M15 6FH. martin.tickle@man.ac.uk

Journal of Public Health Dentistry
|June 21, 2003
PubMed
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Nonresponse bias in postal questionnaire studies can significantly skew results, even with high response rates. This study found that analyzing mailing stage trends provided a more accurate estimate of the true population mean for decayed, missing, and filled teeth (dmft) than socioeconomic status measures.

Area of Science:

  • Dental Public Health
  • Epidemiology
  • Survey Methodology

Background:

  • Postal questionnaires are common in health research, but nonresponse can introduce bias.
  • Estimating population parameters accurately requires addressing potential biases from nonrespondents.
  • Previous methods for bias correction may not fully account for the characteristics of nonresponders.

Purpose of the Study:

  • To compare different methods for detecting and correcting nonresponse bias in postal questionnaire data.
  • To evaluate the effectiveness of using mailing stage and socioeconomic status as predictors of nonresponse.
  • To determine the most accurate method for estimating population means in the presence of nonresponse.

Main Methods:

  • A clinical survey of 5-year-old children collected data on decayed, missing, and filled teeth (dmft).

Related Experiment Videos

  • Postal questionnaires were sent in three stages to target nonresponders, with data available for all children.
  • Estimates of population dmft were generated using methodologies comparing dmft with response stage and area socioeconomic status measures.

    • Main Results:

    • A response rate of 80.9% was achieved, but nonrespondents had a significantly higher mean dmft (2.41) compared to responders (1.27).
    • Significant linear trends in dmft and socioeconomic status were observed across mailing stages.
    • The regression method using mailing stage provided the most accurate adjusted dmft estimate (1.42), outperforming socioeconomic status-based methods (1.31-1.32).

    Conclusions:

    • Nonresponse bias can impact study findings even with acceptable response rates (e.g., 80.9%).
    • Researchers should implement and report analyses to detect and correct for nonresponse bias.
    • The mailing stage of response is a valuable covariate for adjusting estimates in postal survey research.