Using R in experimental design with BIBD: an application in health sciences

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorFrancisco, Carla-
Autor(es): dc.creatorOliveira, Amilcar-
Autor(es): dc.creatorFerreira, Agostinho-
Autor(es): dc.creatorOliveira, Teresa A.-
Data de aceite: dc.date.accessioned2025-08-22T11:48:42Z-
Data de disponibilização: dc.date.available2025-08-22T11:48:42Z-
Data de envio: dc.date.issued2023-08-01-
Data de envio: dc.date.issued2023-08-01-
Data de envio: dc.date.issued2016-06-08-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/10400.2/14688-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/10400.2/14688-
Descrição: dc.descriptionConsidering the implementation of an Experimental Design, in any field, the experimenter must pay particular attention and look for the best strategies in the following steps: planning the design selection, conduct the experiments, collect observed data, proceed to analysis and interpretation of results. The focus is on providing both - a deep understanding of the problem under research and a powerful experimental process at a reduced cost. Mainly thanks to the possibility of allowing to separate variation sources, the importance of Experimental Design in Health Sciences is strongly recommended since long time. Particular attention has been devoted to Block Designs and more precisely to Balanced Incomplete Block Designs - in this case the relevance states from the fact that these designs allow testing simultaneously a number of treatments bigger than the block size. Our example refers to a possible study of inter reliability of the Parkinson disease, taking into account the UPDRS (Unified Parkinson’s disease rating scale) in order to test if there are significant differences between the specialists who evaluate the patients performances. Statistical studies on this disease were described for example in Richards et al (1994), where the authors investigate the inter-rater Reliability of the Unified Parkinson’s Disease Rating Scale Motor Examination. We consider a simulation of a practical situation in which the patients were observed by different specialists and the UPDRS on assessing the impact of Parkinson’s disease in patients was observed. Assigning treatments to the subjects following a particular BIBD(9,24,8,3,2) structure, we illustrate that BIB Designs can be used as a powerful tool to solve emerging problems in this area. Once a structure with repeated blocks allows to have some block contrasts with minimum variance, see Oliveira et al. (2006), the design with cardinality 12 was selected for the example. R software was used for computations.-
Descrição: dc.descriptioninfo:eu-repo/semantics/publishedVersion-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherAIP Publishing-
Relação: dc.relation2014 - Strategic Project-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
Palavras-chave: dc.subjectBIBD-
Palavras-chave: dc.subjectHealth sciences-
Palavras-chave: dc.subjectExperimental design-
Palavras-chave: dc.subjectR software-
Título: dc.titleUsing R in experimental design with BIBD: an application in health sciences-
Aparece nas coleções:Repositório Aberto - Universidade Aberta (Portugal)

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