DOI: 10.11606/t.11.2012.tde-08012013-151513
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Modelos não lineares mistos em estudos de degradabilidade ruminal in situ

Abstract: do Santos (Alê), por tudo o que vivemos e passamos juntos, e pelo apoio incondicional em todos os momentos. Em especial, as minhas "maninhas": Marina Rodrigues Maestre (Nina) e Renata Alcarde (Rê), pelos abraços, amizade, amor, companheirismo...enfim, por tudo! Aos amigos distantes e cúmplices: Pâmela Piovesan (Pamelete), Lara de Maschio Carceles (Larinha), Sheila Santana de Brito (Piquena), Marta Colozza Bianchi (Martinha), Fernando Pereira Micena, Cleicimara Regina Módolo Pico (Cleici), que pelas palavras, a… Show more

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“…The authors sought to address the problems of variance heterogeneity and correlations between repeated longitudinal measurements in in situ ruminal degradation kinetic studies by using NLME. From a statistical point of view, similar problems encountered in different contexts and areas can be properly addressed through the use of mixed models, such as seen in J. C. Pinheiro and Bates (2000); Sartrio (2013); Luwanda and Mwambi (2016); Wyzykowski, Custdio, Custdio, Gomes, and Morais (2015); Calama and Montero (2004);and Xu et al (2014). The proposal to apply a mixed effects methodology involving fixed and random effects parameters and the construction of a data (co)variance matrix (Yang, Huang, Trincado, & Meng, 2009) seems adequate to capture between-and within-animal variabilities and allows modeling the degradability of each animal (subject-specific) as the average degradability of all animals (population specific) (Schabenberger & Pierce, 2002).…”
Section: Introductionmentioning
confidence: 99%
“…The authors sought to address the problems of variance heterogeneity and correlations between repeated longitudinal measurements in in situ ruminal degradation kinetic studies by using NLME. From a statistical point of view, similar problems encountered in different contexts and areas can be properly addressed through the use of mixed models, such as seen in J. C. Pinheiro and Bates (2000); Sartrio (2013); Luwanda and Mwambi (2016); Wyzykowski, Custdio, Custdio, Gomes, and Morais (2015); Calama and Montero (2004);and Xu et al (2014). The proposal to apply a mixed effects methodology involving fixed and random effects parameters and the construction of a data (co)variance matrix (Yang, Huang, Trincado, & Meng, 2009) seems adequate to capture between-and within-animal variabilities and allows modeling the degradability of each animal (subject-specific) as the average degradability of all animals (population specific) (Schabenberger & Pierce, 2002).…”
Section: Introductionmentioning
confidence: 99%