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Responsive design for household surveys: tools for actively controlling survey errors and costs

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  • Robert M. Groves
  • Steven G. Heeringa

Abstract

Summary. Over the past few years surveys have expanded to new populations, have incorporated measurement of new and more complex substantive issues and have adopted new data collection tools. At the same time there has been a growing reluctance among many household populations to participate in surveys. These factors have combined to present survey designers and survey researchers with increased uncertainty about the performance of any given survey design at any particular point in time. This uncertainty has, in turn, challenged the survey practitioner's ability to control the cost of data collection and quality of resulting statistics. The development of computer‐assisted methods for data collection has provided survey researchers with tools to capture a variety of process data (‘paradata’) that can be used to inform cost–quality trade‐off decisions in realtime. The ability to monitor continually the streams of process data and survey data creates the opportunity to alter the design during the course of data collection to improve survey cost efficiency and to achieve more precise, less biased estimates. We label such surveys as ‘responsive designs’. The paper defines responsive design and uses examples to illustrate the responsive use of paradata to guide mid‐survey decisions affecting the non‐response, measurement and sampling variance properties of resulting statistics.

Suggested Citation

  • Robert M. Groves & Steven G. Heeringa, 2006. "Responsive design for household surveys: tools for actively controlling survey errors and costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 439-457, July.
  • Handle: RePEc:bla:jorssa:v:169:y:2006:i:3:p:439-457
    DOI: 10.1111/j.1467-985X.2006.00423.x
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    References listed on IDEAS

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    2. Little R.J., 2004. "To Model or Not To Model? Competing Modes of Inference for Finite Population Sampling," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 546-556, January.
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