Quantifying uncertainty about how interventions are assigned would improve impact evaluation in conservation: reply to Rasolofoson 2022.

Gordon Jones, Julia Patricia; Barnes, Megan; Eklund, Johanna; Ferraro, Paul J; Geldmann, Jonas; Oldekop, Johan A; Schleicher, Judith

Gordon Jones, Julia Patricia; Barnes, Megan; Eklund, Johanna; Ferraro, Paul J; Geldmann, Jonas; Oldekop, Johan A; Schleicher, Judith.

Afiliación

Gordon Jones JP; School of Natural Sciences, College of Environmental Science and Engineering, Bangor University, Bangor, UK.
Barnes M; Centre for Environment and Economic Policy, University of Western Australia, Perth, Western Australia, Australia.
Eklund J; Department of Geosciences and Geography, Faculty of Science, University of Helsinki, Helsinki, Finland.
Ferraro PJ; Carey Business School and Department of Environmental Health and Engineering, a joint department of the Bloomberg School of Public Health and the Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Geldmann J; Centre for Macroecology, Evolution and Climate, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
Oldekop JA; Global Development Institute, The University of Manchester, Manchester, UK.
Schleicher J; Department of Geography, University of Cambridge, Cambridge, UK.

Conserv Biol ; 36(6): e14007, 2022 12.

Article en En | MEDLINE | ID: mdl-36178010

Asunto(s)

Conservación de los Recursos Naturales; Modelos Estadísticos; Incertidumbre

Palabras clave

causal inference; counterfactual; hidden bias; impact evaluation; statistical matching

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Modelos Estadísticos / Conservación de los Recursos Naturales Tipo de estudio: Risk_factors_studies Idioma: En Revista: Conserv Biol Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

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