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Transitioning a panel survey from in‐person to predominantly web data collection: Results and lessons learned

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  • Paul P. Biemer
  • Kathleen Mullan Harris
  • Brian J. Burke
  • Dan Liao
  • Carolyn Tucker Halpern

Abstract

Over the last two decades, in‐person interviewing costs continued to increase while the data quality advantages traditionally identified with this data collection mode have faded. Consequently, some longitudinal surveys have begun transitioning from in‐person to web data collection despite risks to data quality and longitudinal comparability. This paper addresses the major issues involved in the transition process and proposes a multi‐sample, multi‐phase responsive design that attempts to minimize the data quality risks while preserving the considerable cost savings promised by the transition. The paper describes the design as it was applied to the National Longitudinal Study of Adolescent to Adult Health (Add Health)—a nationally representative panel survey of around 20,000 adolescents selected from grades 7 to 12 (typically 13 to 18 years of age) in the 1994–95 school year. Also described are key results from several experiments embedded within the design and the analysis of mode effects. Also presented are some lessons learned and recommendations for other in‐person panel surveys that may be contemplating a similar transition to web or mixed‐mode data collection.

Suggested Citation

  • Paul P. Biemer & Kathleen Mullan Harris & Brian J. Burke & Dan Liao & Carolyn Tucker Halpern, 2022. "Transitioning a panel survey from in‐person to predominantly web data collection: Results and lessons learned," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 798-821, July.
  • Handle: RePEc:bla:jorssa:v:185:y:2022:i:3:p:798-821
    DOI: 10.1111/rssa.12750
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    References listed on IDEAS

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    1. 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.
    2. Abowd, John M & Zellner, Arnold, 1985. "Estimating Gross Labor-Force Flows," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 254-283, June.
    3. Lynn, Peter, 2009. "Sample design for Understanding Society," Understanding Society Working Paper Series 2009-01, Understanding Society at the Institute for Social and Economic Research.
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