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Panel Attrition: How Important is Interviewer Continuity?

Author

Listed:
  • Lynn Peter
  • Kaminska Olena

    (Institute for Social and Economic Research, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ, UK)

  • Goldstein Harvey

    (Centre for Multilevel Modelling, University of Bristol. Tyndall Avenue, Bristol, BS8 1TH, UK)

Abstract

We assess whether the probability of a sample member cooperating at a particular wave of a panel survey is greater if the same interviewer is deployed as at the previous wave. Previous research on this topic mainly uses nonexperimental data. Consequently, a) interviewer change is generally nonrandom, and b) continuing interviewers are more experienced by the time of the next wave. Our study is based on a balanced experiment in which both interviewer continuity and experience are controlled. Multilevel multiple membership models are used to explore the effects of interviewer continuity on refusal rate as well as interactions of interviewer continuity with other variables. We find that continuity reduces refusal propensity for younger respondents but not for older respondents, and that this effect depends on the age of the interviewer. This supports the notion that interviewer continuity may be beneficial in some situations, but not necessarily in others.

Suggested Citation

  • Lynn Peter & Kaminska Olena & Goldstein Harvey, 2014. "Panel Attrition: How Important is Interviewer Continuity?," Journal of Official Statistics, Sciendo, vol. 30(3), pages 1-15, September.
    • Handle: RePEc:vrs:offsta:v:30:y:2014:i:3:p:15:n:7
    DOI: 10.2478/jos-2014-0028
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    References listed on IDEAS

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    1. Pamela Campanelli & Colm O'Muircheartaigh, 2002. "The Importance of Experimental Control in Testing the Impact of Interviewer Continuity on Panel Survey Nonresponse," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(2), pages 129-144, May.
    2. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    3. Lynn, Peter, 2012. "The propensity of older respondents to participate in a general purpose survey," Understanding Society Working Paper Series 2012-03, Understanding Society at the Institute for Social and Economic Research.
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    Citations

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    Cited by:

    1. Sadig, Husam, 2014. "Weighting for non-monotonic response pattern in longitudinal surveys," ISER Working Paper Series 2014-34, Institute for Social and Economic Research.
    2. Adrian Chadi, 2019. "Dissatisfied with life or with being interviewed? Happiness and the motivation to participate in a survey," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 53(3), pages 519-553, October.
    3. Lagorio, Carlos, 2016. "Call and response: modelling longitudinal contact and cooperation using Wave 1 call records data," Understanding Society Working Paper Series 2016-01, Understanding Society at the Institute for Social and Economic Research.
    4. Peter Lynn & Pablo Cabrera‐Álvarez & Paul Clarke, 2023. "Sample composition and representativeness on Understanding Society," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 341-359, December.
    5. Tiffany S. Neman, 2023. "When and Why Does Nonresponse Occur? Comparing the Determinants of Initial Unit Nonresponse and Panel Attrition," Working Papers 23-44, Center for Economic Studies, U.S. Census Bureau.
    6. Plewis Ian & Shlomo Natalie, 2017. "Using Response Propensity Models to Improve the Quality of Response Data in Longitudinal Studies," Journal of Official Statistics, Sciendo, vol. 33(3), pages 753-779, September.

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