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Estimating Components of Mean Squared Error to Evaluate the Benefits of Mixing Data Collection Modes

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  • Roberts Caroline

    (Institute of Social Sciences, University of Lausanne, Bâtiment Géopolis, Quartier Mouline, CH-1015 Lausanne, Switzerland.)

  • Vandenplas Caroline

    (Centre for Sociological Research, KU Leuven, Parkstraat 45 – Box 3601, BE-3000 Leuven, Belgium.)

Abstract

Mixed mode data collection designs are increasingly being adopted with the hope that they may reduce selection errors in single mode survey designs. Yet possible reductions in selection errors achieved by mixing modes may be offset by a potential increase in total survey error due to extra measurement error being introduced by the additional mode(s). Few studies have investigated this empirically, however. In the present study, we compute the Mean Squared Error (MSE) for a range of estimates using data from a mode comparison experiment. We compare two mixed mode designs (a sequential web plus mail survey, and a combined concurrent and sequential CATI plus mail survey) with a single mode mail survey. The availability of auxiliary data on the sampling frame allows us to estimate several components of MSE (sampling variance, non-coverage, nonresponse and measurement bias) for a number of sociodemographic and target variables. Overall, MSEs are lowest for the single mode survey, and highest for the CATI plus mail design, though this pattern is not consistent across all estimates. Mixing modes generally reduces total bias, but the relative contribution to total survey error from different sources varies by design and by variable type.

Suggested Citation

  • Roberts Caroline & Vandenplas Caroline, 2017. "Estimating Components of Mean Squared Error to Evaluate the Benefits of Mixing Data Collection Modes," Journal of Official Statistics, Sciendo, vol. 33(2), pages 303-334, June.
    • Handle: RePEc:vrs:offsta:v:33:y:2017:i:2:p:303-334:n:2
    DOI: 10.1515/jos-2017-0016
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    References listed on IDEAS

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    1. Siemiatycki, J., 1979. "A comparison of mail, telephone, and home interview strategies for household health surveys," American Journal of Public Health, American Public Health Association, vol. 69(3), pages 238-245.
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