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An Analysis of Interviewer Travel and Field Outcomes in Two Field Surveys

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Listed:
  • Wagner James

    (University of Michigan, Institute for Social Research, 426 Thompson St. Room 4050, Ann Arbor, MI 48104, USA)

  • Olson Kristen

    (University of Nebraska-Lincoln, Department of Sociology, 703 Oldfather Hall, Lincoln, NE 68588, USA)

Abstract

In this article, we investigate the relationship between interviewer travel behavior and field outcomes, such as contact rates, response rates, and contact attempts in two studies, the National Survey of Family Growth and the Health and Retirement Study. Using call record paradata that have been aggregated to interviewer-day levels, we examine two important cost drivers as measures of interviewer travel behavior: the distance that interviewers travel to segments and the number of segments visited on an interviewer-day. We explore several predictors of these measures of travel - the geographic size of the sampled areas, measures of urbanicity, and other sample and interviewer characteristics. We also explore the relationship between travel and field outcomes, such as the number of contact attempts made and response rates.We find that the number of segments that are visited on each interviewer-day has a strong association with field outcomes, but the number of miles travelled does not. These findings suggest that survey organizations should routinely monitor the number of segments that interviewers visit, and that more direct measurement of interviewer travel behavior is needed.

Suggested Citation

  • Wagner James & Olson Kristen, 2018. "An Analysis of Interviewer Travel and Field Outcomes in Two Field Surveys," Journal of Official Statistics, Sciendo, vol. 34(1), pages 211-237, March.
    • Handle: RePEc:vrs:offsta:v:34:y:2018:i:1:p:211-237:n:10
    DOI: 10.1515/jos-2018-0010
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    References listed on IDEAS

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    1. Durrant, Gabriele B. & Steele, Fiona, 2009. "Multilevel modelling of refusal and non-contact in household surveys: evidence from six UK Government surveys," LSE Research Online Documents on Economics 50112, London School of Economics and Political Science, LSE Library.
    2. Gabriele B. Durrant & Fiona Steele, 2009. "Multilevel modelling of refusal and non‐contact in household surveys: evidence from six UK Government surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(2), pages 361-381, April.
    3. Annelies G. Blom, 2012. "Explaining cross‐country differences in survey contact rates: application of decomposition methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(1), pages 217-242, January.
    4. Annelies G. Blom & Edith D. de Leeuw & Joop J. Hox, 2010. "Interviewer Effects on Nonresponse," MEA discussion paper series 10202, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    5. Jan Pickery & Geert Loosveldt, 2002. "A Multilevel Multinomial Analysis of Interviewer Effects on Various Components of Unit Nonresponse," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(4), pages 427-437, November.
    6. Paul P. Biemer & Patrick Chen & Kevin Wang, 2013. "Using level-of-effort paradata in non-response adjustments with application to field surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(1), pages 147-168, January.
    7. Barry Schouten & Fannie Cobben & Peter Lundquist & James Wagner, 2016. "Does more balanced survey response imply less non-response bias?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 727-748, June.
    8. C. O'Muircheartaigh & P. Campanelli, 1999. "A multilevel exploration of the role of interviewers in survey non‐response," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(3), pages 437-446.
    9. Weeks, M.F. & Kulka, R.A. & Lessler, J.T. & Whitmore, R.W., 1983. "Personal versus telephone surveys for collecting household health data at the local level," American Journal of Public Health, American Public Health Association, vol. 73(12), pages 1389-1394.
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