DataSHIELD: taking the analysis to the data, not the data to the analysis

Background: Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises...

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Detalhes bibliográficos
Publicado no:Int J Epidemiol
Main Authors: Gaye, Amadou, Marcon, Yannick, Isaeva, Julia, LaFlamme, Philippe, Turner, Andrew, Jones, Elinor M, Minion, Joel, Boyd, Andrew W, Newby, Christopher J, Nuotio, Marja-Liisa, Wilson, Rebecca, Butters, Oliver, Murtagh, Barnaby, Demir, Ipek, Doiron, Dany, Giepmans, Lisette, Wallace, Susan E, Budin-Ljøsne, Isabelle, Oliver Schmidt, Carsten, Boffetta, Paolo, Boniol, Mathieu, Bota, Maria, Carter, Kim W, deKlerk, Nick, Dibben, Chris, Francis, Richard W, Hiekkalinna, Tero, Hveem, Kristian, Kvaløy, Kirsti, Millar, Sean, Perry, Ivan J, Peters, Annette, Phillips, Catherine M, Popham, Frank, Raab, Gillian, Reischl, Eva, Sheehan, Nuala, Waldenberger, Melanie, Perola, Markus, van den Heuvel, Edwin, Macleod, John, Knoppers, Bartha M, Stolk, Ronald P, Fortier, Isabel, Harris, Jennifer R, Woffenbuttel, Bruce HR, Murtagh, Madeleine J, Ferretti, Vincent, Burton, Paul R
Formato: Artigo
Idioma:Inglês
Publicado em: Oxford University Press 2014
Assuntos:
Data Matters
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC4276062/
https://ncbi.nlm.nih.gov/pubmed/25261970
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/ije/dyu188
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