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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Detalles Bibliográficos
Autores principales: 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: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Data Matters
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4276062/
https://www.ncbi.nlm.nih.gov/pubmed/25261970
http://dx.doi.org/10.1093/ije/dyu188

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