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Answering Without Reading: IMCs and Strong Satisficing in Online Surveys

Answering Without Reading: IMCs and Strong Satisficing in Online Surveys AbstractSome respondents of online surveys click responses at random. Screeners or instructional manipulation checks (IMC) have become customary for identifying this strong form of satisficing. This research first analyzes the factors that condition IMC failures using an online panel survey carried out in Spain (2011–2015). Our data show that the probability of passing a screener depends mainly on the screener’s difficulty, the individuals’ intrinsic motivations for answering the survey, and past failures. We then address the substantive consequences of omitting those who fail to pass IMCs. We find that this strategy introduces an additional source of bias in descriptive analyses. The article ends with a discussion of the implications that these findings have for the use of IMCs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Public Opinion Research Oxford University Press

Answering Without Reading: IMCs and Strong Satisficing in Online Surveys

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References (30)

Publisher
Oxford University Press
Copyright
© The Author 2016. Published by Oxford University Press on behalf of The World Association for Public Opinion Research. All rights reserved.
ISSN
0954-2892
eISSN
1471-6909
DOI
10.1093/ijpor/edw007
Publisher site
See Article on Publisher Site

Abstract

AbstractSome respondents of online surveys click responses at random. Screeners or instructional manipulation checks (IMC) have become customary for identifying this strong form of satisficing. This research first analyzes the factors that condition IMC failures using an online panel survey carried out in Spain (2011–2015). Our data show that the probability of passing a screener depends mainly on the screener’s difficulty, the individuals’ intrinsic motivations for answering the survey, and past failures. We then address the substantive consequences of omitting those who fail to pass IMCs. We find that this strategy introduces an additional source of bias in descriptive analyses. The article ends with a discussion of the implications that these findings have for the use of IMCs.

Journal

International Journal of Public Opinion ResearchOxford University Press

Published: Sep 1, 2017

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