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The power of online panel paradata to predict unit nonresponse and voluntary attrition in a longitudinal design

Author

Listed:
  • Sebastian Kocar

    (University of Tasmania)

  • Nicholas Biddle

    (The Australian National University)

Abstract

The objective of this study is to identify factors affecting participation rates, i.e., nonresponse and voluntary attrition rates, and their predictive power in a probability-based online panel. Participation for this panel had already been investigated in the literature according to the socio-demographic and socio-psychological characteristics of respondents and different types of paradata, such as device type or questionnaire navigation, had also been explored. In this study, the predictive power of online panel participation paradata was instead evaluated, which was expected (at least in theory) to offer even more complex insight into respondents’ behavior over time. This kind of paradata would also enable the derivation of longitudinal variables measuring respondents’ panel activity, such as survey outcome rates and consecutive waves with a particular survey outcome prior to a wave (e.g., response, noncontact, refusal), and could also be used in models controlling for unobserved heterogeneity. Using the Life in Australia™ participation data for all recruited members for the first 30 waves, multiple linear, binary logistic and panel random-effect logit regression analyses were carried out to assess socio-demographic and online panel paradata predictors of nonresponse and attrition that were available and contributed to the accuracy of prediction and the best statistical modeling. The proposed approach with the derived paradata predictors and random-effect logistic regression proved to be reasonably accurate for predicting nonresponse—with just 15 waves of online panel paradata (even without sociodemographics) and logit random-effect modeling almost four out of five nonrespondents could be correctly identified in the subsequent wave.

Suggested Citation

  • Sebastian Kocar & Nicholas Biddle, 2023. "The power of online panel paradata to predict unit nonresponse and voluntary attrition in a longitudinal design," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1055-1078, April.
    • Handle: RePEc:spr:qualqt:v:57:y:2023:i:2:d:10.1007_s11135-022-01385-x
    DOI: 10.1007/s11135-022-01385-x
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    References listed on IDEAS

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    1. Cheng Hsiao, 2007. "Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 1-22, May.
    2. Noah Uhrig, S.C., 2008. "The nature and causes of attrition in the British Household Panel Study," ISER Working Paper Series 2008-05, Institute for Social and Economic Research.
    3. Frankel, Laura Lazarus & Hillygus, D. Sunshine, 2014. "Looking Beyond Demographics: Panel Attrition in the ANES and GSS," Political Analysis, Cambridge University Press, vol. 22(3), pages 336-353, July.
    4. Francesco Bartolucci & Valentina Nigro, 2010. "A Dynamic Model for Binary Panel Data With Unobserved Heterogeneity Admitting a √n-Consistent Conditional Estimator," Econometrica, Econometric Society, vol. 78(2), pages 719-733, March.
    5. Couper, Mick P. & Kapteyn, Arie & Schonlau, Matthias & Winter, Joachim, 2007. "Noncoverage and nonresponse in an Internet survey," Munich Reprints in Economics 20093, University of Munich, Department of Economics.
    6. Cheng Hsiao, 2007. "Rejoinder on: Panel data analysis—advantages and challenges," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 56-57, May.
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