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Inattentive Responding in MTurk and Other Online Samples

Published online by Cambridge University Press:  28 July 2015

Avi Fleischer ,
Alan D. Mead  and
Jialin Huang
Avi Fleischer*
Affiliation:
Tetrics LLC, Chicago, Illinois
Alan D. Mead
Affiliation:
Talent Algorithms Inc., Chicago, Illinois
Jialin Huang
Affiliation:
Illinois Institute of Technology
*
Correspondence concerning this article should be addressed to Avi Fleischer, Tetrics LLC, Chicago, IL. E-mail: fleischer@tetrics.com
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Extract

The focal article by Landers and Behrend (2015) makes the case that samples collected on microtask websites like Amazon's Mechanical Turk (MTurk) are inherently no better or worse than traditional samples of convenience from university students or organizations. We wholeheartedly agree. However, having successfully used MTurk and other online sources for data collection, we feel that the focal article was insufficient regarding the caution required in identifying inattentive respondents and the problems that can arise if such individuals are not removed from the dataset. Although we focus on MTurk, similar issues arise for most “low-stakes” assessments, including student samples, which seem to be increasingly collected online.

Type
Commentaries
Information
Industrial and Organizational Psychology , Volume 8 , Issue 2 , June 2015 , pp. 196 - 202
Copyright
Copyright © Society for Industrial and Organizational Psychology 2015 

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