Modelling the�growth curve of�Maine-Anjou beef cattle 
using�heteroskedastic random coefficients�models

Robert-Grani�, Christ�le; Heude, Barbara; Foulley, Jean-Louis

doi:10.1051/gse:2002016

Cited by 4 publications

(4 citation statements)

References 30 publications

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“…Verbeke and Molenberghs [34] showed that this estimator is consistent as long as the mean is correctly specified in the model. In agreement with Robert-Granié et al [29], the results we obtained with this approach showed that, in most cases, the robust standard error was smaller than the naïve one.…”

Section: Model Selectionsupporting

confidence: 93%

Character process model for semen volume in AI rams: evaluation of correlation structures for long and short-term environmental effects

David¹,

Bodin²,

Lagriffoul

et al. 2007

Genet. Sel. Evol.

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The objective of this study was to build a character process model taking into account serial correlations for the analysis of repeated measurements of semen volume in AI rams. For each ram, measurements were repeated within and across years. Therefore, we considered a model including three environmental effects: the long-term environmental effect, which is a random year* subject effect, the short-term environmental effect, which is a random within year subject* collection effect, and the classical measurement error. We used a four-step approach to build the model. The first step explored graphically the serial correlations. The second step compared four models with different correlation structures for the short-term environmental effect. We selected fixed effects in the third step. In the fourth step, we compared four correlation structures for the long-term environmental effect. The model, which fitted best the data, used a spatial power correlation structure for the short-term environmental effect and a first order autoregressive process for the long-term environmental effect. The heritability estimate was 0.27 (0.04), the within year repeatability decreased from 0.56 to 0.44 and the repeatability across years decreased from 0.43 to 0.37.

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Section: Model Selectionsupporting

confidence: 93%

Character process model for semen volume in AI rams: evaluation of correlation structures for long and short-term environmental effects

David¹,

Bodin²,

Lagriffoul

et al. 2007

Genet. Sel. Evol.

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“…Currently random regression models are being applied in the analysis of longitudinal growth in cattle (MEYER 1999, ALBUqUERqUE and MEYER 2001, ROBERT-GRANIé et al 2002, KREJčOVá et al 2007 sheep (LEWIS and BROTHERSTONE 2002, FARHANGFAR et al 2007, KESBI et al 2008 pig (HUISMAN et al 2002) and test-day lactation (JAMROZIK and SCHAEFFER 1997, OLORI et al 1999, KETTUNEN et al 2000, POOL and MEUWISSEN 2000, TAKIMA and AKBAŞ 2007 data. These models use polynomials in time to describe mean profiles with random coefficients to generate a correlation among the repeated observations on each individual (ROBERT-GRANIé et al 2002). This approach has the advantage of studying change and increases statistical power.…”

Section: Introductionmentioning

confidence: 99%

Estimates of (co)variance function for growth to yearling in Horro sheep of Ethiopia using random regression model

2010

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Abstract. Random regression analyses of weight data from birth to 396 days were done using 22 141 weight records of 1 951 Horro lambs. Six different models formed from three different orthogonal polynomial regressions (legendre scale)orders (quadratic, cubic, quartic) of fit for both additive genetic and animals’ permanent environmental effects, with assumption of either homogeneous or heterogeneous residual variance, were compared. Fixed effects of year and type of birth, sex and age of dam were fitted along with a fourth order polynomial. Both likelihood ratio test (LRT) and Akaike's Information Criterion (AIC) were used for model comparison. Model fit improved with increased order of polynomial and assumption of heterogeneity of residual variance. Components for additive genetic and permanent environmental (co)variance increased from 0.03 and 0.09 at birth to 23.8 and 37.6 at 396 days of age, respectively. The first three eigenvalues of the coefficient matrix of the additive genetic covariance accounted for about 98 % of the sum of all the eigenvalues. Heritability estimates have shown a declining and increasing trend at different parts of the trajectory, the lowest estimate being 0.14 for weight at birth while the highest being 0.36 for weight at about 390 days of age. Higher heritability estimates in previous uni- and bi-variate models and in the current study and also strong correlation with weight at early age makes weight at one year of age the most important trait to consider in improving productivity in Horro sheep.

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“…Currently RRM is being applied for genetic evaluation in growth trait such cattle (KREJCOVA et al, 2007;NESER et al, 2012;BOHLOULI et al, 2013), sheep (LEWIS and BROTHERSTON, 2002;GHAFOURI KESBI et al, 2008;ABEGAZ et al, 2010;KARIUKI et al, 2010;WOLC et al, 2011 ) and pig (HUISMAN et al, 2002) data. These models use polynomials in time to describe mean profiles with random coefficients to generate a correlation among the repeated observations on each individual (ROBERT GRANIE et al, 2002). Random regression models are better than multi-trait models, because they allow appropriate modeling of the genetic parameters by avoiding age pre-adjustment, feasibility of taking into account of specific environmental effects on the time of recording, decreasing of the generation interval, increasing of accuracy of breeding values, feasibility of calculating variance for every age and covariance among any pair of ages (MEYER, 2005;SCHAEFFER, 2004).…”

Section: Introductionmentioning

confidence: 99%

Genetic evaluation of growth traits in Iranian Kordi Sheep using random regression model with homogeneous and heterogeneous residual variances

Mohammadi

Farhadian

2017

Genetika

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The purpose of this study was estimation of genetic parameter using random regression model (RRM) with various error variance in Iranian Kordi sheep. The data (consisting of 7875 weight records from birth to 360 days of age) were collected during the period 2000 to 2013 from the rearing and breeding station of Kordi sheep in Shirvan, Iran. The independent variables were Legendre polynomials (LP) of age at weighing and orders of fit from 2 to 5 were considered. Analyses were carried out fitting sets of random regression coefficients due to direct additive genetic, direct and maternal permanent environmental effects, with heterogeneous and homogeneous error variances. To compare the model were used different criteria such as LogL, AIC, BIC and LRT. The best fitting RRM among homogeneous error variance was the model with a LP of fourth order for fixed effect, fourth order for direct additive genetic and fifth order for direct and maternal permanent environmental effects (model 4455). Among the models with heterogeneous error variances different, model 7 (Heterogeneous error variances of 72 various classes), was selected as the best model. The variances increased along the trajectory from 3.75 to 12.81, 4.43 to 30.28 and 1.49 to 8.49; 0.25 to 27.94, 0.03 to 12.32 and 0.15 to 22.66 for direct additive genetic, direct and maternal permanent environmental effect by homogeneous and heterogeneous error variances, respectively. The direct heritability ranged from 0.15 to 0.41 and 0.11 to 0.56 by homogeneous and heterogeneous error variances, respectively. Genetic correlation between adjacent test days was more than between distant test days. This research has demonstrated the possibility of application of RRM with heterogeneous error variance for genetic evaluation of Iranian Kordi Sheep.

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Modelling the�growth curve of�Maine-Anjou beef cattle using�heteroskedastic random coefficients�models

Cited by 4 publications

References 30 publications

Character process model for semen volume in AI rams: evaluation of correlation structures for long and short-term environmental effects

Character process model for semen volume in AI rams: evaluation of correlation structures for long and short-term environmental effects

Estimates of (co)variance function for growth to yearling in Horro sheep of Ethiopia using random regression model

Genetic evaluation of growth traits in Iranian Kordi Sheep using random regression model with homogeneous and heterogeneous residual variances

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