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dc.creatorPereira, Geraldo Magela da Cruz-
dc.creatorMartins Filho, Sebastião-
dc.creatorVeroneze, Renata-
dc.creatorBrito, Luiz Fernando-
dc.creatorSantos, Vinícius Silva dos-
dc.creatorGlória, Leonardo Siqueira-
dc.date.accessioned2024-11-08T17:10:47Z-
dc.date.available2024-11-08T17:10:47Z-
dc.date.issued2023-
dc.identifier.citationPEREIRA, Geraldo Magela da Cruz et al. Alternative measures to evaluate the accuracy and bias of genomic predictions with censored records. Acta Scientiarum. Animal Sciences, [S.l.], v. 45, n. 1, 2023.pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/59674-
dc.description.abstractThis study aimed to propose and compare metrics ofaccuracy and bias of genomic prediction of breeding values for traits with censored data. Genotypic andcensored-phenotypic information were simulated for four traitswith QTL heritability and polygenic heritability, respectively: C1: 0.07-0.07, C2: 0.07-0.00, C3: 0.27-0.27, and C4: 0.27-0.00. Genomic breedingvalues were predicted using the Mixed Cox and Truncated Normal models. The accuracy of the models was estimated based on the Pearson (PC), maximal (MC),and Pearson correlation for censored data (PCC) while the genomic bias was calculated via simple linear regression (SLR) and Tobit (TB). MC and PCCwere statistically superior to PC for the traitC3 with 10and 40% censored information, for 70% censorship, PCC yielded better results than MC and PC. For the other traits, the proposed measures were superior or statistically equal to the PC. The coefficients associated with the marginal effects (TB) presented estimates close to those obtained for the SLRmethod, while the coefficient related to the latent variable showed almost unchanged pattern with the increase in censorship in most cases. From a statistical point of view, the use of methodologiesfor censored data should be prioritized, even for low censoringpercentagespt_BR
dc.languageen_USpt_BR
dc.rightsacesso abertopt_BR
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceActa Scientiarum. Animal Sciencespt_BR
dc.subjectGenomic selectionpt_BR
dc.subjectStatistical modelingpt_BR
dc.subjectSimulationpt_BR
dc.subjectMixed Cox modelpt_BR
dc.subjectTruncated normal modelpt_BR
dc.titleAlternative measures to evaluate the accuracy and bias of genomic predictions with censored recordspt_BR
dc.typeArtigopt_BR
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