Examining the generalizability of research findings from archival data

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dc.citation.issue30
dc.citation.volume119
dc.contributor.authorDelios A
dc.contributor.authorClemente EG
dc.contributor.authorWu T
dc.contributor.authorTan H
dc.contributor.authorWang Y
dc.contributor.authorGordon M
dc.contributor.authorViganola D
dc.contributor.authorChen Z
dc.contributor.authorDreber A
dc.contributor.authorJohannesson M
dc.contributor.authorPfeiffer T
dc.contributor.authorGeneralizability Tests Forecasting Collaboration
dc.contributor.authorUhlmann EL
dc.coverage.spatialUnited States
dc.date.accessioned2024-01-11T00:10:51Z
dc.date.accessioned2024-07-25T06:52:12Z
dc.date.available2022-07-19
dc.date.available2024-01-11T00:10:51Z
dc.date.available2024-07-25T06:52:12Z
dc.date.issued2022-07-26
dc.description.abstractThis initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples.
dc.format.paginatione2120377119-
dc.identifier.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/35858443
dc.identifier.citationDelios A, Clemente EG, Wu T, Tan H, Wang Y, Gordon M, Viganola D, Chen Z, Dreber A, Johannesson M, Pfeiffer T, Generalizability Tests Forecasting Collaboration , Uhlmann EL. (2022). Examining the generalizability of research findings from archival data.. Proc Natl Acad Sci U S A. 119. 30. (pp. e2120377119-).
dc.identifier.doi10.1073/pnas.2120377119
dc.identifier.eissn1091-6490
dc.identifier.elements-typejournal-article
dc.identifier.issn0027-8424
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/71069
dc.languageeng
dc.publisherPNAS
dc.relation.isPartOfProc Natl Acad Sci U S A
dc.rights(c) 2022 The Author/s
dc.rightsCC BY-NC-ND 4.0
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectarchival data
dc.subjectcontext sensitivity
dc.subjectgeneralizability
dc.subjectreproducibility
dc.subjectresearch reliability
dc.titleExamining the generalizability of research findings from archival data
dc.typeJournal article
pubs.elements-id454778
pubs.organisational-groupOther
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