Response Rates, Nonresponse Bias, and Data Quality

Abstract

Survey response rate is regarded as a key data-quality indicator, yet response rate is not necessarily predictive of nonresponse bias. Our study objective was to use a high-response-rate survey to assess nonresponse bias across successive waves. This survey of healthcare leaders utilized a web-based, self-report format with an initial invitation and four nonrespondent follow-ups. Across five waves, comparisons were made for demographic and facility characteristics, proportion of items completed, and distribution of three question types: factual reports of customized categorical responses; single-item evaluations using five-point Likert scales; and multi-item scales, across four-or five-point Likert scales. The overall response rate was 95 percent (118/124); waves did not differ by demographic and facility characteristics or missing data. Across waves, there were no significant differences between responses to two factual report questions or the single-or multi-item scale measures of attitudes. According to a "what-if" analysis of cumulative results by wave, the same conclusions would have been reached if data collection had been halted at earlier points in time. Precision and statistical