IDEAS home Printed from https://ideas.repec.org/a/cup/polals/v28y2020i2p263-283_7.html
   My bibliography  Save this article

Multi-modes for Detecting Experimental Measurement Error

Author

Listed:
  • Duch, Raymond
  • Laroze, Denise
  • Robinson, Thomas
  • Beramendi, Pablo

Abstract

Experiments should be designed to facilitate the detection of experimental measurement error. To this end, we advocate the implementation of identical experimental protocols employing diverse experimental modes. We suggest iterative nonparametric estimation techniques for assessing the magnitude of heterogeneous treatment effects across these modes. And we propose two diagnostic strategies—measurement metrics embedded in experiments, and measurement experiments—that help assess whether any observed heterogeneity reflects experimental measurement error. To illustrate our argument, first we conduct and analyze results from four identical interactive experiments: in the lab; online with subjects from the CESS lab subject pool; online with an online subject pool; and online with MTurk workers. Second, we implement a measurement experiment in India with CESS Online subjects and MTurk workers.

Suggested Citation

  • Duch, Raymond & Laroze, Denise & Robinson, Thomas & Beramendi, Pablo, 2020. "Multi-modes for Detecting Experimental Measurement Error," Political Analysis, Cambridge University Press, vol. 28(2), pages 263-283, April.
    • Handle: RePEc:cup:polals:v:28:y:2020:i:2:p:263-283_7
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1047198719000342/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Roberto Cerina & Raymond Duch, 2021. "Polling India via regression and post-stratification of non-probability online samples," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-34, November.

    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:cup:polals:v:28:y:2020:i:2:p:263-283_7. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/pan .

    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.