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metaumbrella: the first comprehensive suite to perform data analysis in umbrella reviews with stratification of the evidence

Authors

  • Corentin J Gosling DysCo Lab, Department of Psychology, Université Paris Nanterre, F-92000 Nanterre, France Laboratoire de Psychopathologie et Processus de Santé, Université de Paris, F-92100 Boulogne-Billancourt, France Centre for Innovation in Mental Health (CIMH), School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK PubMed articlesGoogle scholar articles
  • Aleix Solanes Institut d'Investigacions Biomediques August Pi i Sunyer, University of Barcelona, Barcelona, Spain PubMed articlesGoogle scholar articles
  • Paolo Fusar-Poli Department of Psychosis Studies, King's College London, London, UK Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy PubMed articlesGoogle scholar articles
  • Joaquim Radua Institut d'Investigacions Biomediques August Pi i Sunyer, University of Barcelona, Barcelona, Spain Department of Psychosis Studies, King's College London, London, UK Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Solna, Sweden PubMed articlesGoogle scholar articles
  1. Correspondence to Dr Corentin J Gosling, Psychology, Paris-Nanterre University, 92001 Nanterre, Paris, France; cgosling{at}parisnanterre.fr
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Citation

Gosling CJ, Solanes A, Fusar-Poli P, et al
metaumbrella: the first comprehensive suite to perform data analysis in umbrella reviews with stratification of the evidence
BMJ Ment Health 2023;26:e300534.

Publication history

  • Received June 27, 2022
  • Accepted November 5, 2022
  • First published February 15, 2023.
Online issue publication 
February 15, 2024

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© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.