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Instructional manipulation checks: Detecting satisficing to increase statistical power |
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| Authors: | Daniel M. Oppenheimer Tom Meyvis |
| Affiliation: | a Princeton University, Dept. of Psychology, Green Hall, Princeton, NJ 08540, USA b Stern School of Business, New York University, 8-15 Tisch Hall, New York, NY 10012, USA c Psychology Department, Stanford University, Building 420, Jordan Hall, Stanford, CA 94305, USA |
| Abstract: | Participants are not always as diligent in reading and following instructions as experimenters would like them to be. When participants fail to follow instructions, this increases noise and decreases the validity of their data. This paper presents and validates a new tool for detecting participants who are not following instructions - the Instructional manipulation check (IMC). We demonstrate how the inclusion of an IMC can increase statistical power and reliability of a dataset. |
| Keywords: | Satisficing Instructions Screening Manipulation checks |
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