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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/463| Using collaboration networks to identify authorship bias in meta-analyses | |
| Thiago C Moulin Olavo B Amaral | |
| Novel Coronavirus | |
| Acceso Abierto | |
| Atribución-NoComercial | |
| 10.1101/19001305 | |
| Meta-analytic methods are powerful resources to summarize the existing evidence concerning a given research question, and are widely used in many academic fields. However, meta-analyses can be vulnerable to various sources of bias, which should be considered to avoid inaccuracies. Many of these sources can be related to study authorship, as both methodological choices and researcher bias may lead to deviations in results between different research groups. In this work, we describe a method to objectively attribute study authorship within a given meta-analysis to different research groups by using graph cluster analysis of collaboration networks. We then provide empirical examples of how the research group of origin can impact effect size in distinct types of meta-analyses, demonstrating how non-independence between within-group results can bias effect size estimates if uncorrected. Finally, we show that multilevel random-effects models using research group as a level of analysis can be a simple tool for correcting biases related to study authorship. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ), Grant/Award Numbers: E-26/201.544/2014 and E-26/203.222/2017; and by scholarships of the Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) ### Author Declarations All relevant ethical guidelines have been followed and any necessary IRB and/or ethics committee approvals have been obtained. Not Applicable All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Not Applicable Any clinical trials involved have been registered with an ICMJE-approved registry such as ClinicalTrials.gov and the trial ID is included in the manuscript. Not Applicable I have followed all appropriate research reporting guidelines and uploaded the relevant Equator, ICMJE or other checklist(s) as supplementary files, if applicable. Not Applicable Both our data and code are available as supplementary material, along with instructions for using the code to construct the figures of our article. | |
| Cold Spring Harbor Laboratory Press | |
| 2019 | |
| Preimpreso | |
| https://www.medrxiv.org/content/10.1101/19001305v2 | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
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| Fichero | Tamaño | Formato | |
|---|---|---|---|
| Using collaboration.pdf | 2.77 MB | Adobe PDF | Visualizar/Abrir |