Balanced prime basis factorial fixed effects model with random number of observations

Bibliographic Details
Main Author: Oliveira, Sandra
Publication Date: 2019
Other Authors: Nunes, Célia, Moreira, Elsa, Fonseca, Miguel, Mexia, João T.
Format: Article
Language: eng
Source: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Download full: http://hdl.handle.net/10400.6/9371
Summary: Factorial designs are in general more efficient for experiments that involve the study of the effects of two or more factors. In this paper we consider a p^U factorial model with U factors, each one having a p prime number of levels. We consider a balanced (r replicates per treatment) prime factorial with fixed effects. Our goal is to extend these models to the case where it is not possible to known in advance the number of treatments replicates, r. In these situations is more appropriate to consider r as a realization of a random variable R, which will be assumed to be geometrically distributed. The proposed approach is illustrated through an application considering simulated data.
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spelling Balanced prime basis factorial fixed effects model with random number of observationsRandom number of replicatesFactorial designsFixed effects modelF distributionFactorial designs are in general more efficient for experiments that involve the study of the effects of two or more factors. In this paper we consider a p^U factorial model with U factors, each one having a p prime number of levels. We consider a balanced (r replicates per treatment) prime factorial with fixed effects. Our goal is to extend these models to the case where it is not possible to known in advance the number of treatments replicates, r. In these situations is more appropriate to consider r as a realization of a random variable R, which will be assumed to be geometrically distributed. The proposed approach is illustrated through an application considering simulated data.uBibliorumOliveira, SandraNunes, CéliaMoreira, ElsaFonseca, MiguelMexia, João T.2020-02-19T14:41:48Z20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.6/9371eng10.1080/02664763.2019.1679097metadata 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:RCAAP2023-12-15T09:50:23Zoai:ubibliorum.ubi.pt:10400.6/9371Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:49:31.550935Repositório 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 Balanced prime basis factorial fixed effects model with random number of observations
title Balanced prime basis factorial fixed effects model with random number of observations
spellingShingle Balanced prime basis factorial fixed effects model with random number of observations
Oliveira, Sandra
Random number of replicates
Factorial designs
Fixed effects model
F distribution
title_short Balanced prime basis factorial fixed effects model with random number of observations
title_full Balanced prime basis factorial fixed effects model with random number of observations
title_fullStr Balanced prime basis factorial fixed effects model with random number of observations
title_full_unstemmed Balanced prime basis factorial fixed effects model with random number of observations
title_sort Balanced prime basis factorial fixed effects model with random number of observations
author Oliveira, Sandra
author_facet Oliveira, Sandra
Nunes, Célia
Moreira, Elsa
Fonseca, Miguel
Mexia, João T.
author_role author
author2 Nunes, Célia
Moreira, Elsa
Fonseca, Miguel
Mexia, João T.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv uBibliorum
dc.contributor.author.fl_str_mv Oliveira, Sandra
Nunes, Célia
Moreira, Elsa
Fonseca, Miguel
Mexia, João T.
dc.subject.por.fl_str_mv Random number of replicates
Factorial designs
Fixed effects model
F distribution
topic Random number of replicates
Factorial designs
Fixed effects model
F distribution
description Factorial designs are in general more efficient for experiments that involve the study of the effects of two or more factors. In this paper we consider a p^U factorial model with U factors, each one having a p prime number of levels. We consider a balanced (r replicates per treatment) prime factorial with fixed effects. Our goal is to extend these models to the case where it is not possible to known in advance the number of treatments replicates, r. In these situations is more appropriate to consider r as a realization of a random variable R, which will be assumed to be geometrically distributed. The proposed approach is illustrated through an application considering simulated data.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-01-01T00:00:00Z
2020-02-19T14:41:48Z
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1080/02664763.2019.1679097
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