Adjusting the Scott-Knott cluster analyses for unbalanced designs

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorConrado, Thiago Vincenzi Thiago Vincenzi-
Autor(es): dc.creatorFerreira, Daniel Furtado-
Autor(es): dc.creatorScapim, Carlos Alberto-
Autor(es): dc.creatorMaluf, Wilson Roberto-
Data de aceite: dc.date.accessioned2026-02-09T11:20:04Z-
Data de disponibilização: dc.date.available2026-02-09T11:20:04Z-
Data de envio: dc.date.issued2018-08-13-
Data de envio: dc.date.issued2018-08-13-
Data de envio: dc.date.issued2017-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/29961-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1138667-
Descrição: dc.descriptionThe Scott-Knott cluster analysis is an alternative approach to mean comparisons with high power and no subset overlapping. It is well suited for the statistical challenges in agronomy associated with testing new cultivars, crop treatments, or methods. The original Scott-Knott test was developed to be used under balanced designs; therefore, the loss of a single plot can significantly increase the rate of type I error. In order to avoid type I error inflation from missing plots, we propose an adjustment that maintains power similar to the original test while adding error protection. The proposed adjustment was validated from more than 40 million simulated experiments following the Monte Carlo method. The results indicate a minimal loss of power with a satisfactory type I error control, while keeping the features of the original procedure. A user-friendly SAS macro is provided for this analysis.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languagept_BR-
Publicador: dc.publisherCrop Breeding and Applied Biotechnology-
Direitos: dc.rightsAttribution 4.0 International-
Direitos: dc.rightsAttribution 4.0 International-
Direitos: dc.rightsacesso aberto-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
???dc.source???: dc.sourceCrop Breeding and Applied Biotechnology-
Palavras-chave: dc.subjectType I error rate-
Palavras-chave: dc.subjectUnequal number of observations-
Palavras-chave: dc.subjectMonte Carlo simulations-
Palavras-chave: dc.subjectMeans clustering procedures-
Título: dc.titleAdjusting the Scott-Knott cluster analyses for unbalanced designs-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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