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Open AccessJournal ArticleDOI

Evaluating survey quality in health services research: a decision framework for assessing nonresponse bias.

Jonathon R. B. Halbesleben, +1 more
- 01 Jun 2013 - 
- Vol. 48, Iss: 3, pp 913-930
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.

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Design, Run, and Interpret Survey-Based Research in the Fields of Academic Integrity and Misconduct

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A Primer on Survey Research

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References
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Posted Content

Estimating Nonresponse Bias in Mail Surveys

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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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.
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