Registro Completo |
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
13/01/2010 |
Data da última atualização: |
19/10/2010 |
Autoria: |
ARAUJO, S. I.; REGAZZI, A. J.; ARAUJO, C. V. de; CRUZ, C. D.; SILVA, C. H. O.; VIANA, J. M. S. |
Afiliação: |
SIMONE INOE ARAUJO, UFMT; ADAIR JOSÉ REGAZZI, UFV; CLAUDIO VIEIRA DE ARAUJO, UFMT; COSME DAMIÃO CRUZ, UFV; CARLOS HENRIQUE OSÓRIO SILVA, UFV; JOSÉ MARCELO SORIANO VIANA, UFV. |
Título: |
Variance component estimation with longitudinal data: a simulation study with alternative methods. |
Ano de publicação: |
2009 |
Fonte/Imprenta: |
Crop Breeding and Applied Biotechnology, Londrina, v. 9, n. 3, p. 202-209, Sept. 2009. |
Idioma: |
Inglês |
Conteúdo: |
A pedigree structure distributed in three different places was generated. For each offspring, phenotypic information was generated for five different ages (12, 30, 48, 66 and 84 months). The data file was simulated allowing some information to be lost (10, 20, 30 and 40%) by a random process and by selecting the ones with lower phenotypic values, representing the selection effect. Three alternative analysis were used, the repeatability model, random regression model and multiple-trait model. Random regression showed to be more adequate to continually describe the covariance structure of growth over time than single-trait and repeatability models, when the assumption of a correlation between successive measurements in the same individual was different from one another. Without selection, random regression and multiple-trait models were very similar. |
Palavras-Chave: |
Modelo de regressão aleatória; Modelo multi-característica; Modelos de repetibilidade; Multiple-trait; Random regression; Selection. |
Thesagro: |
Genética; Seleção; Simulação. |
Thesaurus Nal: |
Repeatability. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01760naa a2200301 a 4500 001 1580220 005 2010-10-19 008 2009 bl uuuu u00u1 u #d 100 1 $aARAUJO, S. I. 245 $aVariance component estimation with longitudinal data$ba simulation study with alternative methods. 260 $c2009 520 $aA pedigree structure distributed in three different places was generated. For each offspring, phenotypic information was generated for five different ages (12, 30, 48, 66 and 84 months). The data file was simulated allowing some information to be lost (10, 20, 30 and 40%) by a random process and by selecting the ones with lower phenotypic values, representing the selection effect. Three alternative analysis were used, the repeatability model, random regression model and multiple-trait model. Random regression showed to be more adequate to continually describe the covariance structure of growth over time than single-trait and repeatability models, when the assumption of a correlation between successive measurements in the same individual was different from one another. Without selection, random regression and multiple-trait models were very similar. 650 $aRepeatability 650 $aGenética 650 $aSeleção 650 $aSimulação 653 $aModelo de regressão aleatória 653 $aModelo multi-característica 653 $aModelos de repetibilidade 653 $aMultiple-trait 653 $aRandom regression 653 $aSelection 700 1 $aREGAZZI, A. J. 700 1 $aARAUJO, C. V. de 700 1 $aCRUZ, C. D. 700 1 $aSILVA, C. H. O. 700 1 $aVIANA, J. M. S. 773 $tCrop Breeding and Applied Biotechnology, Londrina$gv. 9, n. 3, p. 202-209, Sept. 2009.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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