Random sample sizes in orthogonal mixed models with stability

Detalhes bibliográficos
Autor(a) principal: Nunes, Célia
Data de Publicação: 2019
Outros Autores: Mário, Anacleto César Xavier, Ferreira, Dário, Ferreira, Sandra S., Mexia, João T.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.6/9136
Resumo: In this work, we presente a new approach that considers orthogonal mixed models, under situations of stability, when the sample dimensions are not known in advande. In this case, samples are considered realizations of independente rendom variables. We apply this methodology to the case where there is na upper bound for the sample dimensions, which may not be attained since failures may occur. Based on this, we assume that sample sizes are binomially distributed. We consider na application on the incidence of unemployed persons in the European Union to illustrate the proposed methodology. A simulation study is also conduced. The obtained results show the relevance of the proposed approach in avoiding false rejections.
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spelling Random sample sizes in orthogonal mixed models with stabilityBinomial distributionOrthogonal mixed modelsRandom sample sizesStability situationsUnemployment in European UnionIn this work, we presente a new approach that considers orthogonal mixed models, under situations of stability, when the sample dimensions are not known in advande. In this case, samples are considered realizations of independente rendom variables. We apply this methodology to the case where there is na upper bound for the sample dimensions, which may not be attained since failures may occur. Based on this, we assume that sample sizes are binomially distributed. We consider na application on the incidence of unemployed persons in the European Union to illustrate the proposed methodology. A simulation study is also conduced. The obtained results show the relevance of the proposed approach in avoiding false rejections.uBibliorumNunes, CéliaMário, Anacleto César XavierFerreira, DárioFerreira, Sandra S.Mexia, João T.2020-02-07T15:20:51Z20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.6/9136eng10.1002/cmm4.1050metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-15T09:49:44Zoai:ubibliorum.ubi.pt:10400.6/9136Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:49:19.158104Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Random sample sizes in orthogonal mixed models with stability
title Random sample sizes in orthogonal mixed models with stability
spellingShingle Random sample sizes in orthogonal mixed models with stability
Nunes, Célia
Binomial distribution
Orthogonal mixed models
Random sample sizes
Stability situations
Unemployment in European Union
title_short Random sample sizes in orthogonal mixed models with stability
title_full Random sample sizes in orthogonal mixed models with stability
title_fullStr Random sample sizes in orthogonal mixed models with stability
title_full_unstemmed Random sample sizes in orthogonal mixed models with stability
title_sort Random sample sizes in orthogonal mixed models with stability
author Nunes, Célia
author_facet Nunes, Célia
Mário, Anacleto César Xavier
Ferreira, Dário
Ferreira, Sandra S.
Mexia, João T.
author_role author
author2 Mário, Anacleto César Xavier
Ferreira, Dário
Ferreira, Sandra S.
Mexia, João T.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv uBibliorum
dc.contributor.author.fl_str_mv Nunes, Célia
Mário, Anacleto César Xavier
Ferreira, Dário
Ferreira, Sandra S.
Mexia, João T.
dc.subject.por.fl_str_mv Binomial distribution
Orthogonal mixed models
Random sample sizes
Stability situations
Unemployment in European Union
topic Binomial distribution
Orthogonal mixed models
Random sample sizes
Stability situations
Unemployment in European Union
description In this work, we presente a new approach that considers orthogonal mixed models, under situations of stability, when the sample dimensions are not known in advande. In this case, samples are considered realizations of independente rendom variables. We apply this methodology to the case where there is na upper bound for the sample dimensions, which may not be attained since failures may occur. Based on this, we assume that sample sizes are binomially distributed. We consider na application on the incidence of unemployed persons in the European Union to illustrate the proposed methodology. A simulation study is also conduced. The obtained results show the relevance of the proposed approach in avoiding false rejections.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-01-01T00:00:00Z
2020-02-07T15:20:51Z
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1002/cmm4.1050
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