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Abstract:
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Policymakers and researchers rely on large, complex, federally funded, in-person surveys to provide accurate information about a range of issues affecting American life. The quality of information collected in individual data items is as important a measure of the success of these surveys as the more traditional metrics of sample size, response rate, and cost. Interviewers are central to obtaining clear and accurate answers to survey questions, and recruiting the appropriate individuals and training and motivating them to produce high-quality data is a critical element in minimizing survey error. This paper begins by providing an overview of the issues involved. It uses an economic framework to examine the relationships among interviewer characteristics, training, ongoing feedback on data quality, and measures of response quality using a large longitudinal field study database.
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