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dc.contributor.authorDelios, Andrew
dc.contributor.authorClemente, Elena Guilia
dc.contributor.authorWu, Tao
dc.contributor.authorTan, Hongbin
dc.contributor.authorWang, Yong
dc.contributor.authorGordon, Michael
dc.contributor.authorViganola, Domenico
dc.contributor.authorChen, Zhaowei
dc.contributor.authorDreber, Anna
dc.contributor.authorJohannesson, Magnus
dc.contributor.authorPfeiffer, Thomas
dc.contributor.authorGeneralizability Tests Forecasting Collaboration
dc.contributor.authorUhlmann, Eric Luis
dc.identifier.citationDelios , A , Clemente , E G , Wu , T , Tan , H , Wang , Y , Gordon , M , Viganola , D , Chen , Z , Dreber , A , Johannesson , M , Pfeiffer , T , Generalizability Tests Forecasting Collaboration & Uhlmann , E L 2022 , ' Examining the generalizability of research findings from archival data ' , Proceedings of the National Academy of Sciences of the United States of America , vol. 119 , no. 30 , e2120377119 .
dc.identifier.otherPURE: 281293405
dc.identifier.otherPURE UUID: b0806f37-c85f-4880-ba03-af706e3e367d
dc.identifier.otherScopus: 85134491120
dc.identifier.otherORCID: /0000-0003-1147-3025/work/119212600
dc.identifier.otherORCID: /0000-0001-9053-3967/work/121753881
dc.descriptionThis research project benefitted from Ministry of Education (Singapore) Tier 1 Grant R-313-000-131-115 (to A. Delios), National Science Foundation of China Grants 72002158 (to H.T.) and 71810107002 (to H.T.), grants from the Knut and Alice Wallenberg Foundation (to A. Dreber) and the Marianne and Marcus Wallenberg Foundation (through a Wallenberg Scholar grant; to A. Dreber), Austrian Science Fund (FWF) Grant SFB F63 (to A. Dreber), grants from the Jan Wallander and Tom Hedelius Foundation (Svenska Handelsbankens Forskningsstiftelser; to A. Dreber), and an Research & Development (R&D) research grant from Institut Européen d'Administration des Affaires (INSEAD) (to E.L.U.). Dmitrii Dubrov, of the G.T.F.C., was supported by the National Research University Higher School of Economics (HSE University) Basic Research Program.en
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.relation.ispartofProceedings of the National Academy of Sciences of the United States of Americaen
dc.rightsCopyright © 2022 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).en
dc.subjectResearch reliabilityen
dc.subjectArchival dataen
dc.subjectContext sensitivityen
dc.subjectZA4050 Electronic information resourcesen
dc.titleExamining the generalizability of research findings from archival dataen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Economics and Financeen
dc.contributor.institutionUniversity of St Andrews. School of Managementen
dc.description.statusPeer revieweden

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