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dc.contributor.authorMcManus, RM
dc.contributor.authorYoung, L
dc.contributor.authorSweetman, J
dc.date.accessioned2023-09-11T13:28:12Z
dc.date.issued2023-09-07
dc.date.updated2023-09-11T12:49:05Z
dc.description.abstractWhen experimental psychologists make a claim (e.g., “Participants judged X as morally worse than Y”), how many participants are represented? Such claims are often based exclusively on group-level analyses; here, psychologists often fail to report or perhaps even investigate how many participants judged X as morally worse than Y. More troubling, group-level analyses do not necessarily generalize to the person level: “the group-to-person generalizability problem.” We first argue for the necessity of designing experiments that allow investigation of whether claims represent most participants. Second, we report findings that in a survey of researchers (and laypeople), most interpret claims based on group-level effects as being intended to represent most participants in a study. Most believe this ought to be the case if a claim is used to support a general, person-level psychological theory. Third, building on prior approaches, we document claims in the experimental-psychology literature, derived from sets of typical group-level analyses, that describe only a (sometimes tiny) minority of participants. Fourth, we reason through an example from our own research to illustrate this group-to-person generalizability problem. In addition, we demonstrate how claims from sets of simulated group-level effects can emerge without a single participant’s responses matching these patterns. Fifth, we conduct four experiments that rule out several methodology-based noise explanations of the problem. Finally, we propose a set of simple and flexible options to help researchers confront the group-to-person generalizability problem in their own work.en_GB
dc.identifier.citationVol. 6(3)en_GB
dc.identifier.doihttps://doi.org/10.1177/25152459231186615
dc.identifier.urihttp://hdl.handle.net/10871/133967
dc.identifierORCID: 0000-0002-2829-1503 (Sweetman, Joseph)
dc.language.isoenen_GB
dc.publisherSAGE Publicationsen_GB
dc.rights© The Author(s) 2023. Open access. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).en_GB
dc.subjectcognitionen_GB
dc.subjectperson-levelen_GB
dc.subjectprevalenceen_GB
dc.subjectrepeated-measuresen_GB
dc.titlePsychology Is a Property of Persons, Not Averages or Distributions: Confronting the Group-to-Person Generalizability Problem in Experimental Psychologyen_GB
dc.typeArticleen_GB
dc.date.available2023-09-11T13:28:12Z
dc.identifier.issn2515-2459
dc.descriptionThis is the final version. Available on open access from SAGE Publications via the DOI in this recorden_GB
dc.identifier.eissn2515-2467
dc.identifier.journalAdvances in Methods and Practices in Psychological Scienceen_GB
dc.relation.ispartofAdvances in Methods and Practices in Psychological Science, 6(3)
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/en_GB
dcterms.dateAccepted2023-06-14
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2023-09-07
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-09-11T13:25:14Z
refterms.versionFCDVoR
refterms.dateFOA2023-09-11T13:28:14Z
refterms.panelAen_GB
refterms.dateFirstOnline2023-09-07


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© The Author(s) 2023. Open access. 
This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Except where otherwise noted, this item's licence is described as © The Author(s) 2023. Open access. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).