| 1. |
- Glasbey, JC, et al.
(author)
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- 2021
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swepub:Mat__t
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| 2. |
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| 5. |
- Delios, A., et al.
(author)
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Examining the generalizability of research findings from archival data
- 2022
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 119:30
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Journal article (peer-reviewed)abstract
- This 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.
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| 6. |
- Tierney, W., et al.
(author)
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A creative destruction approach to replication : Implicit work and sex morality across cultures
- 2021
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In: Journal of Experimental Social Psychology. - : Elsevier BV. - 0022-1031 .- 1096-0465. ; 93
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Journal article (peer-reviewed)abstract
- How can we maximize what is learned from a replication study? In the creative destruction approach to replication, the original hypothesis is compared not only to the null hypothesis, but also to predictions derived from multiple alternative theoretical accounts of the phenomenon. To this end, new populations and measures are included in the design in addition to the original ones, to help determine which theory best accounts for the results across multiple key outcomes and contexts. The present pre-registered empirical project compared the Implicit Puritanism account of intuitive work and sex morality to theories positing regional, religious, and social class differences; explicit rather than implicit cultural differences in values; self-expression vs. survival values as a key cultural fault line; the general moralization of work; and false positive effects. Contradicting Implicit Puritanism's core theoretical claim of a distinct American work morality, a number of targeted findings replicated across multiple comparison cultures, whereas several failed to replicate in all samples and were identified as likely false positives. No support emerged for theories predicting regional variability and specific individual-differences moderators (religious affiliation, religiosity, and education level). Overall, the results provide evidence that work is intuitively moralized across cultures.
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| 8. |
- Schwarz, E, et al.
(author)
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Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder
- 2019
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In: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 9:1, s. 12-
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Journal article (peer-reviewed)abstract
- Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.
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