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Assessing Nonresponse in a Longitudinal Establishment Survey Using Regression Trees

Author

Listed:
  • Earp Morgan

    (Bureau of Labor Statistics, 2 Massachusetts Avenue NE, Washington DC, 20212-0001, U.S.A.)

  • Toth Daniell

    (Bureau of Labor Statistics, 2 Massachusetts Avenue NE, Washington DC, 20212-0001, U.S.A.)

  • Phipps Polly

    (Bureau of Labor Statistics, 2 Massachusetts Avenue NE, Washington DC, 20212-0001, U.S.A.)

  • Oslund Charlotte

    (Bureau of Labor Statistics, 2 Massachusetts Avenue NE, Washington DC, 20212-0001, U.S.A.)

Abstract

This article introduces and discusses a method for conducting an analysis of nonresponse for a longitudinal establishment survey using regression trees. The methodology consists of three parts: analysis during the frame refinement and enrollment phases, common in longitudinal surveys; analysis of the effect of time on response rates during data collection; and analysis of the potential for nonresponse bias. For all three analyses, regression tree models are used to identify establishment characteristics and subgroups of establishments that represent vulnerabilities during the data collection process. This information could be used to direct additional resources to collecting data from identified establishments in order to improve the response rate.

Suggested Citation

  • Earp Morgan & Toth Daniell & Phipps Polly & Oslund Charlotte, 2018. "Assessing Nonresponse in a Longitudinal Establishment Survey Using Regression Trees," Journal of Official Statistics, Sciendo, vol. 34(2), pages 463-481, June.
    • Handle: RePEc:vrs:offsta:v:34:y:2018:i:2:p:463-481:n:9
    DOI: 10.2478/jos-2018-0021
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    References listed on IDEAS

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    1. F. Kreuter & K. Olson & J. Wagner & T. Yan & T. M. Ezzati‐Rice & C. Casas‐Cordero & M. Lemay & A. Peytchev & R. M. Groves & T. E. Raghunathan, 2010. "Using proxy measures and other correlates of survey outcomes to adjust for non‐response: examples from multiple surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 389-407, April.
    2. repec:mpr:mprres:4937 is not listed on IDEAS
    3. Christian Seiler, 2010. "Dynamic Modelling of Nonresponse in Business Surveys," ifo Working Paper Series 93, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    4. Schouten, Barry & Shlomo, Natalie & Skinner, Chris J., 2011. "Indicators for monitoring and improving representativeness of response," LSE Research Online Documents on Economics 39121, London School of Economics and Political Science, LSE Library.
    5. repec:mpr:mprres:4780 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

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