Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences

Autor: Alec P. Christie, David Abecasis, Mehdi Adjeroud, Juan C. Alonso, Tatsuya Amano, Alvaro Anton, Barry P. Baldigo, Rafael Barrientos, Jake E. Bicknell, Deborah A. Buhl, Just Cebrian, Ricardo S. Ceia, Luciana Cibils-Martina, Sarah Clarke, Joachim Claudet, Michael D. Craig, Dominique Davoult, Annelies De Backer, Mary K. Donovan, Tyler D. Eddy, Filipe M. França, Jonathan P. A. Gardner, Bradley P. Harris, Ari Huusko, Ian L. Jones, Brendan P. Kelaher, Janne S. Kotiaho, Adrià López-Baucells, Heather L. Major, Aki Mäki-Petäys, Beatriz Martín, Carlos A. Martín, Philip A. Martin, Daniel Mateos-Molina, Robert A. McConnaughey, Michele Meroni, Christoph F. J. Meyer, Kade Mills, Monica Montefalcone, Norbertas Noreika, Carlos Palacín, Anjali Pande, C. Roland Pitcher, Carlos Ponce, Matt Rinella, Ricardo Rocha, María C. Ruiz-Delgado, Juan J. Schmitter-Soto, Jill A. Shaffer, Shailesh Sharma, Anna A. Sher, Doriane Stagnol, Thomas R. Stanley, Kevin D. E. Stokesbury, Aurora Torres, Oliver Tully, Teppo Vehanen, Corinne Watts, Qingyuan Zhao, William J. Sutherland
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Nature Communications, Vol 11, Iss 1, Pp 1-11 (2020)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/s41467-020-20142-y
Popis: Randomised controlled experiments are the gold standard for scientific inference, but environmental and social scientists often rely on different study designs. Here the authors analyse the use of six common study designs in the fields of biodiversity conservation and social intervention, and quantify the biases in their estimates.
Databáze: Directory of Open Access Journals