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The Generalizability of Online Experiments Conducted During the COVID-19 Pandemic

Published online by Cambridge University Press:  02 July 2021

Kyle Peyton*
Affiliation:
Institute for Humanities and Social Sciences, Australian Catholic University, Melbourne, Australia
Gregory A. Huber
Affiliation:
Yale University, New Haven, CT, USA
Alexander Coppock
Affiliation:
Yale University, New Haven, CT, USA
*
*Corresponding author. Email: kyle.peyton@acu.edu.au

Abstract

The COVID-19 pandemic imposed new constraints on empirical research, and online data collection by social scientists increased. Generalizing from experiments conducted during this period of persistent crisis may be challenging due to changes in how participants respond to treatments or the composition of online samples. We investigate the generalizability of COVID era survey experiments with 33 replications of 12 pre-pandemic designs, fielded across 13 quota samples of Americans between March and July 2020. We find strong evidence that pre-pandemic experiments replicate in terms of sign and significance, but at somewhat reduced magnitudes. Indirect evidence suggests an increased share of inattentive subjects on online platforms during this period, which may have contributed to smaller estimated treatment effects. Overall, we conclude that the pandemic does not pose a fundamental threat to the generalizability of online experiments to other time periods.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Experimental Research Section of the American Political Science Association

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Footnotes

Kyle Peyton is Research Fellow in Political Science, Institute for Humanities and Social Sciences, Australian Catholic University, Melbourne, Australia (kyle.peyton@acu.edu.au, @pylekeyton); Gregory A. Huber is Forst Family Professor of Political Science, Yale University, New Haven, CT, USA (gregory.huber@yale.edu); Alexander Coppock is Assistant Professor of Political Science, Yale University, New Haven, CT, USA (alex.coppock@yale.edu, @aecoppock).

This article has earned badges for transparent research practices: Open Data and Open Materials. For details see the Data Availability Statement.

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