Instructional Manipulation Checks: Detecting Satisficing to Increase Statistical Power

By Daniel M. Oppenheimer, Tom Meyvis, Nicolas Davidenko. 2009

3,366 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Decision Sciences, Statistics and Probability

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Citations in the corpus

Evaluation of Text Generation: A Survey (2020, background): “However, maintaining quality control online can be an issue (Ipeirotis et al., 2010; Oppenheimer et al., 2009), and the demographics of the evaluators may be heavily skewed depending on user base of the platform (Difallah et al.”
Retribution as Revenge and Retribution as Just Deserts (2013, methodology): “This manipulation was used to screen out people who do random clicking and to increase attention of the remaining participants (Oppenheimer et al., 2009).”
The explanatory effect of a label: Explanations with named categories are more satisfying. (2017, background): “On a separate screen, participants then answered one additional catch question, an instructional manipulation check, designed to ensure that they were reading instructions carefully, modeled after Oppenheimer, Meyvis, and Davidenko (2009).”
Degrees of Freedom in Planning, Running, Analyzing, and Reporting Psychological Studies: A Checklist to Avoid p-Hacking (2016, background): “…participants include awareness checks, as often used in priming research (e.g., the funnel debriefing; Bargh and Chartrand, 2000), checks for alertness in responding like the blue dot task (Oppenheimer et al., 2009), or even the simple question like “did you participate seriously in this study?”.”
Caring about carelessness: Participant inattention and its effects on research. (2014, methodology): “These results are consistent with a growing body of findings (e.g., Johnson, 2005; Meade & Craig, 2012; Oppenheimer et al., 2009; Woods, 2006), suggesting that inattention can obscure both experimental manipulations and correlational results.”