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Demand Effects in Survey Experiments: An Empirical Assessment

Published online by Cambridge University Press:  11 December 2018

JONATHAN MUMMOLO*
Affiliation:
Princeton University
ERIK PETERSON*
Affiliation:
Texas A&M University
*
*Jonathan Mummolo, Assistant Professor of Politics and Public Affairs, Department of Politics and Woodrow Wilson School of Public and International Affairs, Princeton University, jmummolo@princeton.edu.
Erik Peterson, Assistant Professor of Political Science, Department of Political Science, Texas A&M University, erik.peterson@tamu.edu.

Abstract

Survey experiments are ubiquitous in social science. A frequent critique is that positive results in these studies stem from experimenter demand effects (EDEs)—bias that occurs when participants infer the purpose of an experiment and respond so as to help confirm a researcher’s hypothesis. We argue that online survey experiments have several features that make them robust to EDEs, and test for their presence in studies that involve over 12,000 participants and replicate five experimental designs touching on all empirical political science subfields. We randomly assign participants information about experimenter intent and show that providing this information does not alter the treatment effects in these experiments. Even financial incentives to respond in line with researcher expectations fail to consistently induce demand effects. Research participants exhibit a limited ability to adjust their behavior to align with researcher expectations, a finding with important implications for the design and interpretation of survey experiments.

Type
Research Article
Copyright
Copyright © American Political Science Association 2018 

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Footnotes

The authors are grateful for feedback from Adam Berinsky, Cheryl Boudreau, Amber Boydstun, John Bullock, Brandice Canes-Wrone, Justin Esarey, Justin Grimmer, Erin Hartman, Samara Klar, Neil Malhotra, Nolan McCarty, Tali Mendelberg, Sean Westwood, and attendees of the 2017 Society for Political Methodology (PolMeth) annual meeting. Replication materials can be found on the American Political Science Review Dataverse at: https://doi.org/10.7910/DVN/HUKSID.

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