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- ODonnell, Michael, et al.
(författare)
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Registered Replication Report: Dijksterhuis and van Knippenberg (1998)
- 2018
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Ingår i: Perspectives on Psychological Science. - : SAGE PUBLICATIONS LTD. - 1745-6916 .- 1745-6924. ; 13:2, s. 268-294
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Tidskriftsartikel (refereegranskat)abstract
- Dijksterhuis and van Knippenberg (1998) reported that participants primed with a category associated with intelligence (professor) subsequently performed 13% better on a trivia test than participants primed with a category associated with a lack of intelligence (soccer hooligans). In two unpublished replications of this study designed to verify the appropriate testing procedures, Dijksterhuis, van Knippenberg, and Holland observed a smaller difference between conditions (2%-3%) as well as a gender difference: Men showed the effect (9.3% and 7.6%), but women did not (0.3% and -0.3%). The procedure used in those replications served as the basis for this multilab Registered Replication Report. A total of 40 laboratories collected data for this project, and 23 of these laboratories met all inclusion criteria. Here we report the meta-analytic results for those 23 direct replications (total N = 4,493), which tested whether performance on a 30-item general-knowledge trivia task differed between these two priming conditions (results of supplementary analyses of the data from all 40 labs, N = 6,454, are also reported). We observed no overall difference in trivia performance between participants primed with the professor category and those primed with the hooligan category (0.14%) and no moderation by gender.
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2. |
- Aczel, Balazs, et al.
(författare)
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Consensus-based guidance for conducting and reporting multi-analyst studies
- 2021
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Ingår i: eLIFE. - : eLife Sciences Publications. - 2050-084X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.
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3. |
- Huntington-Klein, Nick, et al.
(författare)
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Subjective evidence evaluation survey for many-analysts studies
- 2024
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Ingår i: Royal Society Open Science. - : The Royal Society. - 2054-5703 .- 2054-5703. ; 11:7
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Tidskriftsartikel (refereegranskat)abstract
- Many-analysts studies explore how well an empirical claim withstands plausible alternative analyses of the same dataset by multiple, independent analysis teams. Conclusions from these studies typically rely on a single outcome metric (e.g. effect size) provided by each analysis team. Although informative about the range of plausible effects in a dataset, a single effect size from each team does not provide a complete, nuanced understanding of how analysis choices are related to the outcome. We used the Delphi consensus technique with input from 37 experts to develop an 18-item subjective evidence evaluation survey (SEES) to evaluate how each analysis team views the methodological appropriateness of the research design and the strength of evidence for the hypothesis. We illustrate the usefulness of the SEES in providing richer evidence assessment with pilot data from a previous many-analysts study.
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4. |
- Uhlmann, Eric, L., et al.
(författare)
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Subjective Evidence Evaluation Survey For Multi-Analyst Studies
- 2024
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Multi-analyst studies explore how well an empirical claim withstands plausible alternative analyses of the same data set by multiple, independent analysis teams. Conclusions from these studies typically rely on a single outcome metric (e.g., effect size) provided by each analysis team. Although informative about the range of plausible effects in a data set, a single effect size from each team does not provide a complete, nuanced understanding of how analysis choices are related to the outcome. We used the Delphi consensus technique with input from 37 experts to develop an 18-item Subjective Evidence Evaluation Survey (SEES) to evaluate how each analysis team views the methodological appropriateness of the research design and the strength of evidence for the hypothesis. We illustrate the usefulness of the SEES in providing richer evidence assessment with pilot data from a previous multi-analyst study.
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