Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study

Detalhes bibliográficos
Autor(a) principal: Garcia, Diogo Anastácio [UNESP]
Data de Publicação: 2012
Outros Autores: Pereira, Idalmo Garcia, Fonseca e Silva, Fabyano, Rosa, Guilherme Jordão de Magalhães, Pires, Aldrin Vieira, Leandro, Roseli Aparecida
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1590/S1516-35982012000100008
http://hdl.handle.net/11449/4391
Resumo: The objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.
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spelling Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation studybeef cattleearly pregnancygenetic parametersGLMMlink functionThe objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)UNESP Faculdade de Ciências Agrárias e VeterináriasUFVJM FCA Departamento de ZootecniaUFV Departamento de EstatísticaUniversity of Wisconsin Department of Dairy ScienceESALQ LCE Departamento de Ciências ExatasUNESP Faculdade de Ciências Agrárias e VeterináriasSociedade Brasileira de ZootecniaUniversidade Estadual Paulista (Unesp)Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)UFV Departamento de EstatísticaUniversity of Wisconsin Department of Dairy ScienceUniversidade de São Paulo (USP)Garcia, Diogo Anastácio [UNESP]Pereira, Idalmo GarciaFonseca e Silva, FabyanoRosa, Guilherme Jordão de MagalhãesPires, Aldrin VieiraLeandro, Roseli Aparecida2014-05-20T13:18:13Z2014-05-20T13:18:13Z2012-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article52-57application/pdfhttp://dx.doi.org/10.1590/S1516-35982012000100008Revista Brasileira de Zootecnia. Sociedade Brasileira de Zootecnia, v. 41, n. 1, p. 52-57, 2012.1516-3598http://hdl.handle.net/11449/439110.1590/S1516-35982012000100008S1516-35982012000100008WOS:000300431700008S1516-35982012000100008.pdfSciELOreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRevista Brasileira de Zootecnia0,337info:eu-repo/semantics/openAccess2023-12-19T06:24:24Zoai:repositorio.unesp.br:11449/4391Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-12-19T06:24:24Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study
title Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study
spellingShingle Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study
Garcia, Diogo Anastácio [UNESP]
beef cattle
early pregnancy
genetic parameters
GLMM
link function
title_short Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study
title_full Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study
title_fullStr Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study
title_full_unstemmed Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study
title_sort Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study
author Garcia, Diogo Anastácio [UNESP]
author_facet Garcia, Diogo Anastácio [UNESP]
Pereira, Idalmo Garcia
Fonseca e Silva, Fabyano
Rosa, Guilherme Jordão de Magalhães
Pires, Aldrin Vieira
Leandro, Roseli Aparecida
author_role author
author2 Pereira, Idalmo Garcia
Fonseca e Silva, Fabyano
Rosa, Guilherme Jordão de Magalhães
Pires, Aldrin Vieira
Leandro, Roseli Aparecida
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM)
UFV Departamento de Estatística
University of Wisconsin Department of Dairy Science
Universidade de São Paulo (USP)
dc.contributor.author.fl_str_mv Garcia, Diogo Anastácio [UNESP]
Pereira, Idalmo Garcia
Fonseca e Silva, Fabyano
Rosa, Guilherme Jordão de Magalhães
Pires, Aldrin Vieira
Leandro, Roseli Aparecida
dc.subject.por.fl_str_mv beef cattle
early pregnancy
genetic parameters
GLMM
link function
topic beef cattle
early pregnancy
genetic parameters
GLMM
link function
description The objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.
publishDate 2012
dc.date.none.fl_str_mv 2012-01-01
2014-05-20T13:18:13Z
2014-05-20T13:18:13Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1590/S1516-35982012000100008
Revista Brasileira de Zootecnia. Sociedade Brasileira de Zootecnia, v. 41, n. 1, p. 52-57, 2012.
1516-3598
http://hdl.handle.net/11449/4391
10.1590/S1516-35982012000100008
S1516-35982012000100008
WOS:000300431700008
S1516-35982012000100008.pdf
url http://dx.doi.org/10.1590/S1516-35982012000100008
http://hdl.handle.net/11449/4391
identifier_str_mv Revista Brasileira de Zootecnia. Sociedade Brasileira de Zootecnia, v. 41, n. 1, p. 52-57, 2012.
1516-3598
10.1590/S1516-35982012000100008
S1516-35982012000100008
WOS:000300431700008
S1516-35982012000100008.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Revista Brasileira de Zootecnia
0,337
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 52-57
application/pdf
dc.publisher.none.fl_str_mv Sociedade Brasileira de Zootecnia
publisher.none.fl_str_mv Sociedade Brasileira de Zootecnia
dc.source.none.fl_str_mv SciELO
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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