IDEAS home Printed from https://ideas.repec.org/a/taf/mpopst/v24y2017i3p161-171.html
   My bibliography  Save this article

Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not based on probability schemes

Author

Listed:
  • Vera Toepoel
  • Hannah Emerson

Abstract

Weighting techniques in web surveys based on no probability schemes are devised to correct biases due to self-selection, undercoverage, and nonresponse. In an interactive panel, 38 survey experts addressed weighting techniques and auxiliary variables in web surveys. Most of them corrected all biases jointly and applied calibration and propensity score adjustments. Although they claimed that sociodemographic and web-related variables are the most useful auxiliary variables to employ in adjustments, they considered only sociodemographic variables to correct biases because of their availability.

Suggested Citation

  • Vera Toepoel & Hannah Emerson, 2017. "Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not based on probability schemes," Mathematical Population Studies, Taylor & Francis Journals, vol. 24(3), pages 161-171, July.
  • Handle: RePEc:taf:mpopst:v:24:y:2017:i:3:p:161-171
    DOI: 10.1080/08898480.2017.1330012
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/08898480.2017.1330012
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/08898480.2017.1330012?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. Malhotra, Neil & Krosnick, Jon A., 2007. "The Effect of Survey Mode and Sampling on Inferences about Political Attitudes and Behavior: Comparing the 2000 and 2004 ANES to Internet Surveys with Nonprobability Samples," Political Analysis, Cambridge University Press, vol. 15(3), pages 286-323, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Antonia Moreno & Guillermo Sanz & Begonya Garcia-Zapirain, 2021. "hGLUTEN Tool: Measuring Its Social Impact Indicators," IJERPH, MDPI, vol. 18(23), pages 1-18, December.
    2. Abood Khaled Alamoudi & Rotimi Boluwatife Abidoye & Terence Y. M. Lam, 2023. "Implementing Smart Sustainable Cities in Saudi Arabia: A Framework for Citizens’ Participation towards SAUDI VISION 2030," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    3. Kristina Niedderer & Isabelle Tournier & Laura Orton & Steve Threlfall, 2023. "I Can Do: Co-Designing a Service with and for People with Dementia to Engage with Volunteering," Social Sciences, MDPI, vol. 12(6), pages 1-19, June.

    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. Kevin J. Boyle & Mark Morrison & Darla Hatton MacDonald & Roderick Duncan & John Rose, 2016. "Investigating Internet and Mail Implementation of Stated-Preference Surveys While Controlling for Differences in Sample Frames," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(3), pages 401-419, July.
    2. Lasse J. Jessen & Sebastian Koehne & Patrick Nüß & Jens Ruhose, 2024. "Socioeconomic Inequality in Life Expectancy: Perception and Policy Demand," CESifo Working Paper Series 10940, CESifo.
    3. Aaron C. Sparks & Heather Hodges & Sarah Oliver & Eric R. A. N. Smith, 2020. "Confidence in Local, National, and International Scientists on Climate Change," Sustainability, MDPI, vol. 13(1), pages 1-13, December.
    4. Lindhjem, Henrik & Navrud, Ståle, 2011. "Using Internet in Stated Preference Surveys: A Review and Comparison of Survey Modes," International Review of Environmental and Resource Economics, now publishers, vol. 5(4), pages 309-351, September.
    5. Magdalena Smyk & Joanna Tyrowicz & Lucas van der Velde, 2021. "A Cautionary Note on the Reliability of the Online Survey Data: The Case of Wage Indicator," Sociological Methods & Research, , vol. 50(1), pages 429-464, February.
    6. Guy Grossman & Devorah Manekin & Dan Miodownik, 2013. "The Political Legacies of Combat: Attitudes towards war and peace amongst Israeli ex-combatants," HiCN Working Papers 161, Households in Conflict Network.
    7. Carina Cornesse & Ulrich Krieger & Marie‐Lou Sohnius & Marina Fikel & Sabine Friedel & Tobias Rettig & Alexander Wenz & Sebastian Juhl & Roni Lehrer & Katja Möhring & Elias Naumann & Maximiliane Reife, 2022. "From German Internet Panel to Mannheim Corona Study: Adaptable probability‐based online panel infrastructures during the pandemic," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 773-797, July.
    8. Stefano Visintin & Kea Tijdens & Stephanie Steinmetz & Pablo de Pedraza, 2015. "Task implementation heterogeneity and wage dispersion," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-24, December.
    9. Carina Cornesse & Annelies G. Blom, 2023. "Response Quality in Nonprobability and Probability-based Online Panels," Sociological Methods & Research, , vol. 52(2), pages 879-908, May.
    10. Klick, Holly & Smith, Eric R.A.N., 2010. "Public understanding of and support for wind power in the United States," Renewable Energy, Elsevier, vol. 35(7), pages 1585-1591.
    11. Grewenig, Elisabeth & Lergetporer, Philipp & Simon, Lisa & Werner, Katharina & Woessmann, Ludger, 2023. "Can internet surveys represent the entire population? A practitioners’ analysis," European Journal of Political Economy, Elsevier, vol. 78(C).
    12. Karytsas, Spyridon & Theodoropoulou, Helen, 2014. "Socioeconomic and demographic factors that influence publics' awareness on the different forms of renewable energy sources," Renewable Energy, Elsevier, vol. 71(C), pages 480-485.
    13. Sakshaug Joseph W. & Wiśniowski Arkadiusz & Ruiz Diego Andres Perez & Blom Annelies G., 2019. "Supplementing Small Probability Samples with Nonprobability Samples: A Bayesian Approach," Journal of Official Statistics, Sciendo, vol. 35(3), pages 653-681, September.
    14. Khatun, Farzana & Saphores, Jean-Daniel, 2023. "Covid-19, intentions to change modes, and how they materialized - Results from a random survey of Californians," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    15. Karytsas, Spyridon & Polyzou, Olympia & Karytsas, Constantine, 2019. "Factors affecting willingness to adopt and willingness to pay for a residential hybrid system that provides heating/cooling and domestic hot water," Renewable Energy, Elsevier, vol. 142(C), pages 591-603.
    16. Catherine Chen & Bo MacInnis & Matthew Waltman & Jon A. Krosnick, 2021. "Public opinion on climate change in the USA: to what extent can it be nudged by questionnaire design features?," Climatic Change, Springer, vol. 167(3), pages 1-18, August.
    17. Lehdonvirta, Vili & Oksanen, Atte & Räsänen, Pekka & Blank, Grant, 2020. "Social Media, Web, and Panel Surveys: Using Non- Probability Samples in Social and Policy Research," OSF Preprints qrwg4, Center for Open Science.
    18. repec:aia:aiaswp:wp76 is not listed on IDEAS
    19. Karytsas, Spyridon, 2018. "An empirical analysis on awareness and intention adoption of residential ground source heat pump systems in Greece," Energy Policy, Elsevier, vol. 123(C), pages 167-179.
    20. Jeffrey R. Brown & Arie Kapteyn & Erzo F.P. Luttmer & Olivia Mitchell, 2012. "Do Consumers Know How to Value Annuities? Complexity as a Barrier to Annuitization," Working Papers WR-924-SSA, RAND Corporation.

    More about this item

    Statistics

    Access and download statistics

    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:taf:mpopst:v:24:y:2017:i:3:p:161-171. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GMPS20 .

    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.