Evaluating survey quality in health services research: a decision framework for assessing nonresponse bias.
TLDR
It is important that the quality of survey data be considered to assess the relative contribution to the literature of a given study and the potential effects of nonresponse bias should be considered both before and after survey administration.Abstract:
Objective: To address the issue of nonresponse as problematic and offer appropriate strategies for assessing nonresponse bias. Study Design: A review of current strategies used to assess the quality of survey data and the challenges associated with these strategies is provided along with appropriate post-data collection techniques that researchers should consider. Principal Findings: Response rates are an incomplete assessment of survey data quality and quick reactions to response rate should be avoided. Based on a five-question decision making framework we offer potential ways to assess nonresponse bias along with a description of the advantages and disadvantages to each. Conclusions: It is important that the quality of survey data be considered to assess the relative contribution to the literature of a given study. Authors and funding agencies should consider the potential effects of nonresponse bias both before and after survey administration and report the results of assessments of nonresponse bias in addition to response rates.read more
Citations
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Journal ArticleDOI
Quality and Impact of Survey Research Among Anesthesiologists: A Systematic Review.
Emily D. Geyer,Rebecca Miller,Stephani S. Kim,Joseph D. Tobias,Joseph D. Tobias,Olubukola O. Nafiu,Dmitry Tumin +6 more
TL;DR: The impact of published research based on surveys of anesthesiologists, as measured by citation scores and Altmetrics, may be driven primarily by the novel data or questions raised using survey methodology, but does not appear to be associated with response rates.
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References
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Posted Content
Estimating Nonresponse Bias in Mail Surveys
JS Armstrong,Terry Overton +1 more
TL;DR: Valid predictions for the direction of nonresponse bias were obtained from subjective estimates and extrapolations in an analysis of mail survey data from published studies and the use of extrapolation led to substantial improvements over a strategy of not using extrapolation.
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Statistical Analysis with Missing Data.
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Nonresponse Rates and Nonresponse Bias in Household Surveys
TL;DR: The authors showed that nonresponse bias can be translated into causal models to guide hypotheses about when nonresponse causes bias, but the linkage between nonresponse rates and nonresponse biases is absent.
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Response rates to mail surveys published in medical journals.
TL;DR: Although several mail survey techniques are associated with higher response rates, response rates to published mail surveys tend to be moderate, and investigators, journal editors, and readers should devote more attention to assessments of bias, and less to specific response rate thresholds.