Instructional manipulation checks: Detecting satisficing to increase statistical power

Oppenheimer, Daniel M.; Meyvis, Tom; Davidenko, Nicolas

doi:10.1016/j.jesp.2009.03.009

Cited by 3,493Survey Methodology and NonresponsePsychometric Methodologies and TestingExperimental Behavioral Economics Studies

Instructional manipulation checks: Detecting satisficing to increase statistical power

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Oppenheimer, Daniel M., Meyvis, Tom, Davidenko, Nicolas·2009·Journal of Experimental Social Psychology

DOI 10.1016/j.jesp.2009.03.009

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Among the participants, those who indicated their attention level as 'very little' or 'not at all' were excluded from the analysis, leaving a final sample of N = 211.
“Among the participants, those who indicated their attention level as”
From Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation (2025) · cites this paper as [74]
An instructional manipulation check (IMC) was used to improve the quality of participant responses.
“In order to improve the quality of participant responses, we utilized an instructional manipulation check (IMC) (Oppenheimer et al., 2009).”
From Sluggish Cognitive Tempo and Personality: Links to BIS/BAS Sensitivity and the Five Factor Model (2018) · cites this paper as Oppenheimer et al., 2009
Attention checks are an important method for enhancing data quality, particularly when utilizing online platforms such as Prolific.
“an important method for enhancing data quality67, particularly when utilizing online platforms such as Prolific66.”
From Establishing the importance of co-creation and self-efficacy in creative collaboration with artificial intelligence (2024) · cites this paper as [67]

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Authors: Oppenheimer, D. M., Meyvis, T., & Davidenko, N.
Affiliations: University of California, Los Angeles (US)
New York University (US)
Stanford University (US)
Corresponding author: Oppenheimer, Daniel M.
ORCID: Oppenheimer, Daniel M.
Meyvis, Tom
Davidenko, Nicolas
Venue: Journal of Experimental Social Psychology
Publisher: Elsevier BV
Published: 2009-07
Volume: 45
Issue: 4
Pages: 867-872
ISSN: 0022-1031 (ISSN-L)
DOI: 10.1016/j.jesp.2009.03.009
OpenAlex: W2152427206
Cited by: 3,493
References: 19
Citations by year: 2026: 231 · 2025: 304 · 2024: 262 · 2023: 283 · 2022: 304 · 2021: 356 · 2020: 304 · 2019: 277 · 2018: 246 · 2017: 248 · 2016: 168 · 2015: 182 · 2014: 141 · 2013: 97 · 2012: 47
FWCI: 92.00
Type: journal article
Language: en
Open access: green
papers.ssrn.com
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Journal of Experimental Social Psychology (publishedVersion)
SSRN Electronic Journal (submittedVersion)
Topics: Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Social Sciences › Safety Research › Experimental Behavioral Economics Studies
Keywords: participant compliance, satisficing, statistical power, reliability statistics, data validity, noisy data

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