IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v57y2023i2d10.1007_s11135-022-01385-x.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-022-01385-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11135-022-01385-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hany Eldemerdash & Hugh Metcalf & Sara Maioli, 2014. "Twin deficits: new evidence from a developing (oil vs. non-oil) countries’ perspective," Empirical Economics, Springer, vol. 47(3), pages 825-851, November.
    2. Ding Luo & Oded Cats & Hans Lint, 2020. "Can passenger flow distribution be estimated solely based on network properties in public transport systems?," Transportation, Springer, vol. 47(6), pages 2757-2776, December.
    3. Li, Larry & McMurray, Adela & Sy, Malick & Xue, Jinjun, 2018. "Corporate ownership, efficiency and performance under state capitalism: Evidence from China," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 747-766.
    4. Dzintra Atstāja & Edmira Cakrani, 2024. "Impact of Climate Change on International Tourism Evidence from Baltic Sea Countries," Sustainability, MDPI, vol. 16(12), pages 1-16, June.
    5. Lynn, Peter & Bosch, Oriol, 2021. "Methodological lessons from the pilot longitudinal survey on debt advice," ISER Working Paper Series 2021-03, Institute for Social and Economic Research.
    6. Yasser Razak Hussain & Pranab Mukhopadhyay, 2023. "How Much do Education, Experience, and Social Networks Impact Earnings in India? A Panel Data Analysis Disaggregated by Class, Gender, Caste and Religion," SAGE Open, , vol. 13(4), pages 21582440231, December.
    7. Trabelsi, Emna & Hichri, Walid, 2021. "Central Bank Transparency with (semi-)public Information: Laboratory Experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
    8. Noor Zainab.Tunggal & Shariff Umar Shariff Abd. Kadir & Venus-Khim Sen Liew, 2018. "Panel Analysis of Monetary Model of ASEAN-5 Exchange Rates," International Business Research, Canadian Center of Science and Education, vol. 11(11), pages 1-7, November.
    9. Wanglin Ma & Kathryn Bicknell & Alan Renwick, 2019. "Feed use intensification and technical efficiency of dairy farms in New Zealand," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(1), pages 20-38, January.
    10. Martey, Edward & Etwire, Prince Maxwell & Abdoulaye, Tahirou, 2020. "Welfare impacts of climate-smart agriculture in Ghana: Does row planting and drought-tolerant maize varieties matter?," Land Use Policy, Elsevier, vol. 95(C).
    11. Wenhao Song & Chunhui Ye & Yuheng Liu & Weisong Cheng, 2021. "Do China’s Urban–Environmental Quality and Economic Growth Conform to the Environmental Kuznets Curve?," IJERPH, MDPI, vol. 18(24), pages 1-15, December.
    12. Elkhan Richard Sadik-Zada & Wilhelm Loewenstein, 2020. "Drivers of CO 2 -Emissions in Fossil Fuel Abundant Settings: (Pooled) Mean Group and Nonparametric Panel Analyses," Energies, MDPI, vol. 13(15), pages 1-24, August.
    13. Vishal Gupta & Sandra C. Mortal & Tina Yang, 2018. "Entrepreneurial orientation and firm value: Does managerial discretion play a role?," Review of Managerial Science, Springer, vol. 12(1), pages 1-26, January.
    14. Aina B. Aidarova & Gulzada Mukhamediyeva & Aizhan A. Yessentayeva & Guliya Utemissova & Karlygash Tastanbekova & Bagila Mustafayeva & Kundyz Myrzabekkyzy, 2024. "Relationship between Oil Exports, Renewable Energy Consumption, Agriculture Industry, and Economic Growth in Selected OPEC Countries: A Panel ARDL Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 14(6), pages 344-352, November.
    15. Merello, Paloma & Barberá, Antonio & la Poza, Elena De, 2022. "Is the sustainability profile of FinTech companies a key driver of their value?," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    16. Yuanyuan Qu & Aza Azlina Md Kassim, 2023. "The Impact of Economic Policy Uncertainty on Investment in Real Estate Corporations Based on Sustainable Development: The Mediating Role of House Prices," Sustainability, MDPI, vol. 15(21), pages 1-17, October.
    17. Saldivia, Mauricio & Kristjanpoller, Werner & Olson, Josephine E., 2020. "Energy consumption and GDP revisited: A new panel data approach with wavelet decomposition," Applied Energy, Elsevier, vol. 272(C).
    18. Shuang Meng & Pengxiang Wang & Jiajie Yu, 2022. "Going Abroad and Going Green: The Effects of Top Management Teams’ Overseas Experience on Green Innovation in the Digital Era," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    19. Migbaru Alamirew Workneh & Zerayehu Sime Eshete, 2021. "Household Level Non-Monetary Poverty in Ethiopia and its Driving Factors: a Multidimensional Approach with Panel Estimation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(1), pages 145-168, February.
    20. Thompson, Kristina & Ophem, Johan van & Wagemakers, Annemarie, 2019. "Studying the impact of the Eurozone’s Great Recession on health: Methodological choices and challenges," Economics & Human Biology, Elsevier, vol. 35(C), pages 162-184.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:57:y:2023:i:2:d:10.1007_s11135-022-01385-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.