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Why Hypothesis Testers Should Spend Less Time Testing Hypotheses
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Abstract
For almost half a century, Paul Meehl educated psychologists about how the mindless use of null-hypothesis significance tests made research on theories in the social sciences basically uninterpretable. In response to the replication crisis, reforms in psychology have focused on formalizing procedures for testing hypotheses. These reforms were necessary and influential. However, as an unexpected consequence, psychological scientists have begun to realize that they may not be ready to test hypotheses. Forcing researchers to prematurely test hypotheses before they have established a sound "derivation chain" between test and theory is counterproductive. Instead, various nonconfirmatory research activities should be used to obtain the inputs necessary to make hypothesis tests informative. Before testing hypotheses, researchers should spend more time forming concepts, developing valid measures, establishing the causal relationships between concepts and the functional form of those relationships, and identifying boundary conditions and auxiliary assumptions. Providing these inputs should be recognized and incentivized as a crucial goal in itself. In this article, we discuss how shifting the focus to nonconfirmatory research can tie together many loose ends of psychology's reform movement and help us to develop strong, testable theories, as Paul Meehl urged.
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“Due to this lack of theory and robust data, we as AI researchers might simply not be ready to test specific hypotheses for certain contexts-a conclusion that is not unheard of in other research fields, such as psychology (Scheel et al., 2021) and human-robot interaction (Leichtmann et al., 2022).”
From Effects of Explainable Artificial Intelligence on trust and human behavior in a high-risk decision task (2023) · cites this paper as Scheel et al., 2021
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“Scheel et al. (2021) suggested that, before testing hypotheses confirmatorily, prior steps such as exploratory experimentation can help to discover relationships between variables and to explore boundaries on the basis of which more concrete theoretical assumptions can be made.”
From Effects of Explainable Artificial Intelligence on trust and human behavior in a high-risk decision task (2023) · cites this paper as Scheel et al., 2021
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“Thus, it becomes evident that more specific theorizing enables more precise operationalizations and more adequate empirical testing (Scheel et al., 2021).”
From Do Salient Social Norms Moderate Mortality Salience Effects? A (Challenging) Meta-Analysis of Terror Management Studies (2023) · cites this paper as Scheel et al., 2021
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“Even though the studies have confirmed the significance and influence of BPN Satisfaction for HCI research, the inconsistent use of measures is problematic in terms of comparability between studies and their replicability.”
From Development and Validation of a Basic Psychological Needs Scale for Technology Use (2024) · cites this paper as Scheel et al. (2021)
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“If a study fails to apply a valid measure, theoretical inferences cannot be made as the findings could equally measure random noise or a related but nevertheless distinct construct (Scheel et al., 2021).”
From Development and Validation of a Basic Psychological Needs Scale for Technology Use (2024) · cites this paper as Scheel et al., 2021
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“The causal model of kama muta—its proximal causes and consequences as well as its evolved function—was inspired by relational models theory (Fiske, 2004).”
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Metadata
- Authors
- Scheel, A. M., Tiokhin, L., Isager, P. M., & Lakens, D.
- Affiliations
- Eindhoven University of Technology (NL)
- Corresponding author
- Scheel, Anne M.
- Venue
- Perspectives on Psychological Science
- Publisher
- SAGE Publications
- Published
- 2020-12-16
- Volume
- 16
- Issue
- 4
- Pages
- 744-755
- ISSN
- 1745-6916 (ISSN-L)
- 1745-6924
- PMC
- PMC8273364
- OpenAlex
- W3113132966
- Cited by
- 382
- References
- 95
- Citations by year
- 2026: 32 · 2025: 48 · 2024: 82 · 2023: 69 · 2022: 80 · 2021: 59 · 2020: 12
- FWCI
- 143.27
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Perspectives on Psychological Science (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- TU/e Research Portal (publishedVersion, cc-by)
- PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
- PsyArXiv (OSF Preprints) (submittedVersion)
- TU/e Research Portal (submittedVersion, cc-by)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VIDI grant 452-17-013)
- Topics
- Social Sciences › Psychology › General Psychology › Academic and Historical Perspectives in Psychology
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- null hypothesis significance testing, hypothesis testing, replication crisis, Paul Meehl, theory testing, measurement validity, auxiliary hypotheses, boundary conditions
- MeSH terms
- Humans, Psychological Theory, Psychology, Causality
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