Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences
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 quanti...
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Nature Portfolio
2020
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oai:doaj.org-article:c3f8aa3f77e54f6fa535672c92afaa442021-12-02T10:48:10ZQuantifying and addressing the prevalence and bias of study designs in the environmental and social sciences10.1038/s41467-020-20142-y2041-1723https://doaj.org/article/c3f8aa3f77e54f6fa535672c92afaa442020-12-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-20142-yhttps://doaj.org/toc/2041-1723Randomised 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.Alec P. ChristieDavid AbecasisMehdi AdjeroudJuan C. AlonsoTatsuya AmanoAlvaro AntonBarry P. BaldigoRafael BarrientosJake E. BicknellDeborah A. BuhlJust CebrianRicardo S. CeiaLuciana Cibils-MartinaSarah ClarkeJoachim ClaudetMichael D. CraigDominique DavoultAnnelies De BackerMary K. DonovanTyler D. EddyFilipe M. FrançaJonathan P. A. GardnerBradley P. HarrisAri HuuskoIan L. JonesBrendan P. KelaherJanne S. KotiahoAdrià López-BaucellsHeather L. MajorAki Mäki-PetäysBeatriz MartínCarlos A. MartínPhilip A. MartinDaniel Mateos-MolinaRobert A. McConnaugheyMichele MeroniChristoph F. J. MeyerKade MillsMonica MontefalconeNorbertas NoreikaCarlos PalacínAnjali PandeC. Roland PitcherCarlos PonceMatt RinellaRicardo RochaMaría C. Ruiz-DelgadoJuan J. Schmitter-SotoJill A. ShafferShailesh SharmaAnna A. SherDoriane StagnolThomas R. StanleyKevin D. E. StokesburyAurora TorresOliver TullyTeppo VehanenCorinne WattsQingyuan ZhaoWilliam J. SutherlandNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-11 (2020) |
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DOAJ |
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EN |
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Science Q |
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Science Q 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 Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences |
| description |
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. |
| format |
article |
| author |
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 |
| author_facet |
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 |
| author_sort |
Alec P. Christie |
| title |
Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences |
| title_short |
Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences |
| title_full |
Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences |
| title_fullStr |
Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences |
| title_full_unstemmed |
Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences |
| title_sort |
quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences |
| publisher |
Nature Portfolio |
| publishDate |
2020 |
| url |
https://doaj.org/article/c3f8aa3f77e54f6fa535672c92afaa44 |
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