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  4. A propensity score approach in the impact evaluation on scientific production in Brazilian biodiversity research: the BIOTA Program
Please use this identifier to cite or link to this item: https://repositorio.insper.edu.br/handle/11224/4166
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dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DOS USUÁRIOS INDIVIDUAIS VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITORpt_BR
dc.date.accessioned2022-10-07T14:39:02Z-
dc.date.available2022-10-07T14:39:02Z-
dc.date.issued2014-
dc.identifier.issn1588-2861pt_BR
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/4166-
dc.format.extentp. 85–107pt_BR
dc.format.mediumDigitalpt_BR
dc.language.isoInglêspt_BR
dc.publisherAkadémiai Kiadópt_BR
dc.relation.ispartofScientometricspt_BR
dc.relation.urihttps://link.springer.com/article/10.1007/s11192-014-1397-1pt_BR
dc.titleA propensity score approach in the impact evaluation on scientific production in Brazilian biodiversity research: the BIOTA Programpt_BR
dc.typeArtigo Científicopt_BR
dc.description.otherEvaluation has become a regular practice in the management of science, technology and innovation (ST&I) programs. Several methods have been developed to identify the results and impacts of programs of this kind. Most evaluations that adopt such an approach conclude that the interventions concerned, in this case ST&I programs, had a positive impact compared with the baseline, but do not control for any effects that might have improved the indicators even in the absence of intervention, such as improvements in the socio-economic context. The quasi-experimental approach therefore arises as an appropriate way to identify the real contributions of a given intervention. This paper describes and discusses the utilization of propensity score (PS) in quasi-experiments as a methodology to evaluate the impact on scientific production of research programs, presenting a case study of the BIOTA Program run by FAPESP, the State of São Paulo Research Foundation (Brazil). Fundamentals of quasi-experiments and causal inference are presented, stressing the need to control for biases due to lack of randomization, also a brief introduction to the PS estimation and weighting technique used to correct for observedcbias. The application of the PS methodology is compared to the traditional multivariatecanalysis usually employed.pt_BR
dc.subject.cnpqCiências Exatas e da Terrapt_BR
dc.subject.keywordsQuasi-experimentpt_BR
dc.subject.keywordsPropensity scorept_BR
dc.subject.keywordsImpact evaluationpt_BR
dc.subject.keywordsBiota programpt_BR
dc.subject.keywordsBibliometricspt_BR
dc.identifier.doihttps://doi.org/10.1007/s11192-014-1397-1pt_BR
dc.identifier.volume101pt_BR
dc.description.notesTrabalho Completopt_BR
dc.contributor.autorFirpo, Sergio Pinheiro-
dc.contributor.autorColugnati, Fernando A. B.-
dc.contributor.autorCastro, Paula F. Drummond de-
dc.contributor.autorSepulveda, Juan E.-
dc.contributor.autorSalles-Filho, Sergio L. M.-
dc.coverage.paisHungriapt_BR
dc.coverage.cidadeBudapestpt_BR
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