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Sökning: WFRF:(Howe Aaron) > (2020-2024)

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1.
  • Nielsen, Wils, et al. (författare)
  • OMERACT 2023 Systemic Lupus Erythematosus Special Interest Group : Winnowing and Binning Preliminary Candidate Domains for the Core Outcome Set
  • 2024
  • Ingår i: Seminars in Arthritis & Rheumatism. - : Elsevier. - 0049-0172 .- 1532-866X. ; 65
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: The Outcome Measures in Rheumatology (OMERACT) Systemic Lupus Erythematosus (SLE) Working Group held a Special Interest Group (SIG) at the OMERACT 2023 conference in Colorado Springs where SLE collaborators reviewed domain sub-themes generated through qualitative research and literature review.OBJECTIVE: The objective of the SIG and the subsequent meetings of the SLE Working Group was to begin the winnowing and binning of candidate domain sub-themes into a preliminary list of candidate domains that will proceed to the consensus Delphi exercise for the SLE COS.METHODS: Four breakout groups at the SLE SIG in Colorado Springs winnowed and binned 132 domain sub-themes into candidate domains, which was continued with a series of virtual meetings by an advisory group of SLE patient research partners (PRPs), members of the OMERACT SLE Working Group Steering Committee, and other collaborators.RESULTS: The 132 domain sub-themes were reduced to a preliminary list of 20 candidate domains based on their clinical and research relevance for clinical trials and research studies.CONCLUSION: A meaningful and substantial winnowing and binning of candidate domains for the SLE COS was achieved resulting in a preliminary list of 20 candidate domains.
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2.
  • Grossmann, Igor, et al. (författare)
  • Insights into the accuracy of social scientists' forecasts of societal change
  • 2023
  • Ingår i: Nature Human Behaviour. - : Springer Nature. - 2397-3374. ; 7, s. 484-501
  • Tidskriftsartikel (refereegranskat)abstract
    • How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists' forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data. How accurate are social scientists in predicting societal change, and what processes underlie their predictions? Grossmann et al. report the findings of two forecasting tournaments. Social scientists' forecasts were on average no more accurate than those of simple statistical models.
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