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Assessment of variance components in nonlinear mixed-effects elliptical models

Russo, Cibele Maria; Aoki, Reiko; Paula, Gilberto Alvarenga
Fonte: Springer; New York Publicador: Springer; New York
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
66.07%
The issue of assessing variance components is essential in deciding on the inclusion of random effects in the context of mixed models. In this work we discuss this problem by supposing nonlinear elliptical models for correlated data by using the score-type test proposed in Silvapulle and Silvapulle (1995). Being asymptotically equivalent to the likelihood ratio test and only requiring the estimation under the null hypothesis, this test provides a fairly easy computable alternative for assessing one-sided hypotheses in the context of the marginal model. Taking into account the possible non-normal distribution, we assume that the joint distribution of the response variable and the random effects lies in the elliptical class, which includes light-tailed and heavy-tailed distributions such as Student-t, power exponential, logistic, generalized Student-t, generalized logistic, contaminated normal, and the normal itself, among others. We compare the sensitivity of the score-type test under normal, Student-t and power exponential models for the kinetics data set discussed in Vonesh and Carter (1992) and fitted using the model presented in Russo et al. (2009). Also, a simulation study is performed to analyze the consequences of the kurtosis misspecification.; FAPESP; CNPq...

Componentes de variância e valores genéticos para as produções de leite do dia do controle e da lactação na raça holandesa com diferentes modelos estatísticos.; Variance components and breeding value for test day and lactation milk yields in holstein cattle with different statistical models.

Melo, Claudio Manoel Rodrigues de
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 15/07/2003 PT
Relevância na Pesquisa
56.07%
Foram utilizados 263.390 registros de produção de leite do dia do controle (PDC) de 32.448 primeiras lactações de vacas da raça Holandesa obtidas no período de 1991 a 2001 para estimar componentes de variância e parâmetros genéticos, usando diferentes modelos estatísticos e a metodologia REML. Compararam-se as estimativas de valores genético (EVG) dos modelos de repetibilidade (MR) e de regressão aleatória (MRA) com às do modelo para as produções da lactação (P305). Nos MRA utilizaram-se duas curvas para descrever a trajetória da lactação: a polinomial logarítmica de Ali e Schaeffer (AS) e a exponencial de Wilmink (W), sob duas formas: a padrão e com uma modificação para reduzir a amplitude das covariáveis e contornar problemas de convergência (W Ú ). No ajuste da curva AS considerou-se heterogeneidade de variâncias residuais (VR) entre classes de dias em lactação (cDEL). A estimativa de herdabilidade para as P305 (0,27) foi menor do que àquelas para as PDC obtidas com MR, incluindo ou não a curva AS como sub modelo (0,30 e 0,43, repectivamente). As herdabilidades para as PDC por análises uni-caráter (0,22-0,36) e bi-caráter (0,23-0,33) foram menores no início e fim da lactação. As correlações genéticas entre produções de controles consecutivos foram superiores às estimadas entre controles do ínicio e do fim da lactação. As estimativas de herdabilidade por MRA com as curva AS (0...

Componentes de (co)variância e parâmetros genéticos para caracteristicas de crescimento de bovinos da raça Guzerá usando diferentes estratégias de análise.; (CO)Variance components and genetic parameters for growth traits in guzera breed by different analysis of strategies.

Silva, Itiberê Saldanha
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 25/11/2004 PT
Relevância na Pesquisa
66.23%
Foram utilizados arquivos com 104.101, 55.063 e 60.782 registros de pesos corporais, do nascimento aos 630 de idades, de bovinos da raça Guzerá, da Associação Brasileira dos Criadores de Zebu (ABCZ), referentes ao período de 1975 a 2001, para estimar componentes de (co)variância e parâmetros genéticos, de acordo com três abordagens de análise, cada uma com um arquivo, utilizando diferentes modelos estatísticos e a metodologia REML. Nestas abordagens foram obtidos valores das estimativas de variância e parâmetros genéticos de modelos unicaracterísticos; modelos uni e bicaracterísticos e, de modelos de regressão aleatória (MRA), respectivamente. Na primeira, com quatro modelos unicaraterísticos, observou-se que o modelo 1, considerado completo, por incluir os efeitos genéticos direto e materno (GM) e os efeitos de ambiente permanente materno e residual, não diferiu significativamente (P<0,05), pelo teste razão de verossimilhança do modelo 2, que exclui o GM. As herdabilidades diretas (h2) estimadas nos modelos 1 e 2, foram muito semelhantes. Os valores de h2 cresceram da primeira idade até a segunda idade, mantiveram os valores até o desmame e depois cresceram. As estimativas de variância genética materna foram baixas...

Simulação de dados visando à estimação de componentes de variância e coeficientes de herdabilidade; Simulation of data aiming at the estimation of variance components and heritability

Coelho, Angela Mello
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 03/02/2006 PT
Relevância na Pesquisa
66.3%
A meta principal desse trabalho foi comparar métodos de estimação para coeficientes de herdabilidade para os modelos inteiramente ao acaso e em blocos casualizados. Para os dois casos foram utilizadas as definições de coeficiente de herdabilidade (h2) no sentido restrito, dadas respectivamente, por h2=4 σ2t/(σ2+σ2t) e h2=4 σ2t/(σ2+σ2t+σ2b). . Portanto, é preciso estimar os componentes de variância relativos ao erro experimental (σ2) e ao efeito de tratamentos (σ2t) quando se deseja estimar h2 para o modelo inteiramente ao acaso. Para o modelo para blocos casualizados, além de estimar os últimos dois componentes, é necessário estimar o componente de variância relativo ao efeito de blocos (σ2b). Para atingir a meta estabelecida, partiu-se de um conjunto de dados cujo coeficiente de herdabilidade é conhecido, o que foi feito através da simulação de dados. Foram comparados dois métodos de estimação, o método da análise da variância e método da máxima verossimilhança. Foram feitas 80 simulações, 40 para cada ensaio. Para os dois modelos, as 40 simulações foram divididas em 4 casos contendo 10 simulações. Cada caso considerou um valor distinto para h2...

Testes de hipóteses para componentes de variância utilizando estatísticas U; U-tests for variance components in linear mixed models.

Nobre, Juvencio Santos
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 09/08/2007 PT
Relevância na Pesquisa
66.07%
Nós consideramos decomposições de estatísticas $U$ para obter testes para componentes de variância. As distribuições assintóticas das estatísticas de testes sob a hipótese nula são obtidas supondo apenas a existência do quarto momento do erro condicional e do segundo momento dos efeitos aleatórios. Isso permite sua utilização em uma classe bastante ampla de distribuições. Sob a suposição adicional de existência do quarto momento dos efeitos aleatórios, obtemos também a distribuição assintótica das estatísticas sob uma seqüência de hipóteses alternativas locais. Comparamos a eficiência dos testes propostos com aqueles dos testes clássicos, obtidos sob suposição de normalidade, por meio de estudos de simu-lação. Os testes propostos se mostram mais adequados nas situações em que a amostra é de tamanho moderado ou grande, independentemente da distribuição das fontes de variação, e nas situações em que existe fortes afastamentos da normalidade.; We consider decompositions of U-statistics to obtain tests for null variance components in linear mixed models. Their asymptotic distributions under the null hypothesis are obtained only assuming the existence of the first four moments of the conditional error distribution and the existence of the first two moments of the random effects distribution. Thus...

Comparação de rols classificatórios de tratamentos e de estimativas de componentes de variância em grupos de experimentos; Comparison of treatments classicatory rankings and of variance components estimates in experimental groups

Dessotti, Cássio
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 28/01/2010 PT
Relevância na Pesquisa
56.21%
As análises de grupos de experimentos, de grande importância em melhoramento genético, são indispensáveis quando se pretende investigar o comportamento de alguns tratamentos em diversos locais de interesse do pesquisador. Nestes casos, parte-se das analises de variância individuais em cada local, para o agrupamento de todos os ensaios em uma única analise. Verifica-se então a veracidade da significância da interação tratamentos versus locais - TL, sendo esta não-significativa, pode-se obter conclusões generalizados a respeito do comportamento dos tratamentos. No entanto, o grande interesse esta nos casos de interação significativa, em que dois caminhos de destaque surgem para que se conclua a analise, o primeiro, permite que se considerem os resultados e conclusões das analises individuais, com o resíduo específico de cada local, enquanto o segundo aconselha que se desdobrem os graus de liberdade relativos a tratamentos + interação significativa, visando a interpretação dos tratamentos em estudo dentro de cada um dos locais, utilizando o resíduo médio como testador. Partindo do fato de que componentes de variância são variâncias associadas aos efeitos aleatórios de um modelo matemático, que permitem quantificar a variabilidade de tais efeitos...

Comparação de métodos de estimação de componentes de variância e parâmetros genéticos considerando o delineamento III aplicado a caracteres quantitativos em milho; Comparison of estimation methods for variance components and genetic parameters considering the Design III applied to quantitative characters in maize

Coelho, Angela Mello
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 09/04/2010 PT
Relevância na Pesquisa
66.32%
Esse trabalho teve como objetivo comparar métodos de estimação de componentes de variância e parâmetros genéticos, considerando tanto o delineamento estatístico fatorial instalado em látice quadrado como o delineamento genético III. Como referência, foram utilizados três conjuntos de dados reais, em melhoramento genético de milho, relativos aos caracteres de produção de grãos (gramas por parcela), altura da folha bandeira ao chão (centímetros) e o número de folhas entre a primeira espiga e o pendão; sendo que a altura da folha bandeira e o número de folhas foram obtidos pela média entre cinco plantas competitivas para cada parcela. O método da Análise da Variância (ANOVA), conforme indicado pelo Delineameno III, foi utilizado na análise dos dados e estimação dos componentes de variância relativos ao modelo matemático, variâncias genéticas, coeficiente de herdabilidade e grau médio de dominância para cada um dos três caracteres estudados. Essas estimativas foram utilizadas na simulação de 1000 conjuntos de dados com características semelhantes a cada um dos conjuntos de dado reais considerados. Os métodos da ANOVA e da máxima verossimilhança restrita (REML) foram utilizados na predição dos parâmetros já mencionados para cada um dos conjuntos de dados simulados dentro de cada caráter. As 1000 estimativas obtidas por cada método...

Modeling strategies for complex hierarchical and overdispersed data in the life sciences; Estratégias de modelagem para dados hierárquicos complexos e com superdispersão em ciências biológicas

Oliveira, Izabela Regina Cardoso de
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 24/07/2014 EN
Relevância na Pesquisa
46.27%
In this work, we study the so-called combined models, generalized linear mixed models with extension to allow for overdispersion, in the context of genetics and breeding. Such flexible models accommodates cluster-induced correlation and overdispersion through two separate sets of random effects and contain as special cases the generalized linear mixed models (GLMM) on the one hand, and commonly known overdispersion models on the other. We use such models while obtaining heritability coefficients for non-Gaussian characters. Heritability is one of the many important concepts that are often quantified upon fitting a model to hierarchical data. It is often of importance in plant and animal breeding. Knowledge of this attribute is useful to quantify the magnitude of improvement in the population. For data where linear models can be used, this attribute is conveniently defined as a ratio of variance components. Matters are less simple for non-Gaussian outcomes. The focus is on time-to-event and count traits, where the Weibull-Gamma-Normal and Poisson-Gamma-Normal models are used. The resulting expressions are sufficiently simple and appealing, in particular in special cases, to be of practical value. The proposed methodologies are illustrated using data from animal and plant breeding. Furthermore...

Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

Mota, R. R.; Marques, L. F A; Lopes, P. S.; da Silva, L. P.; Neto, F. R A; de Resende, M. D V; Torres, R. A.
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Artigo de Revista Científica Formato: 2465-2480
ENG
Relevância na Pesquisa
46.21%
The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude...

Variance components for body weight in Japanese quails (Coturnix japonica)

Resende,RO; Martins,EN; Georg,PC; Paiva,E; Conti,ACM; Santos,AI; Sakaguti,ES; Murakami,AE
Fonte: Fundação APINCO de Ciência e Tecnologia Avícolas Publicador: Fundação APINCO de Ciência e Tecnologia Avícolas
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/03/2005 EN
Relevância na Pesquisa
46.31%
The objective of this study was to estimate the variance components for body weight in Japanese quails by Bayesian procedures. The body weight at hatch (BWH) and at 7 (BW07), 14 (BW14), 21 (BW21) and 28 days of age (BW28) of 3,520 quails was recorded from August 2001 to June 2002. A multiple-trait animal model with additive genetic, maternal environment and residual effects was implemented by Gibbs sampling methodology. A single Gibbs sampling with 80,000 rounds was generated by the program MTGSAM (Multiple Trait Gibbs Sampling in Animal Model). Normal and inverted Wishart distributions were used as prior distributions for the random effects and the variance components, respectively. Variance components were estimated based on the 500 samples that were left after elimination of 30,000 rounds in the burn-in period and 100 rounds of each thinning interval. The posterior means of additive genetic variance components were 0.15; 4.18; 14.62; 27.18 and 32.68; the posterior means of maternal environment variance components were 0.23; 1.29; 2.76; 4.12 and 5.16; and the posterior means of residual variance components were 0.084; 6.43; 22.66; 31.21 and 30.85, at hatch, 7, 14, 21 and 28 days old, respectively. The posterior means of heritability were 0.33; 0.35; 0.36; 0.43 and 0.47 at hatch...

The variance composition of firm growth rates

Brito,Luiz Artur Ledur; Vasconcelos,Flávio Carvalho de
Fonte: ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração Publicador: ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/06/2009 EN
Relevância na Pesquisa
56.15%
Firms exhibit a wide variability in growth rates. This can be seen as another manifestation of the fact that firms are different from one another in several respects. This study investigated this variability using the variance components technique previously used to decompose the variance of financial performance. The main source of variation in growth rates, responsible for more than 40% of total variance, corresponds to individual, idiosyncratic firm aspects and not to industry, country, or macroeconomic conditions prevailing in specific years. Firm growth, similar to financial performance, is mostly unique to specific firms and not an industry or country related phenomenon. This finding also justifies using growth as an alternative outcome of superior firm resources and as a complementary dimension of competitive advantage. This also links this research with the resource-based view of strategy. Country was the second source of variation with around 10% of total variance. The analysis was done using the Compustat Global database with 80,320 observations, comprising 13,221 companies in 47 countries, covering the years of 1994 to 2002. It also compared the variance structure of growth to the variance structure of financial performance in the same sample

Heterogeneous genetic (co)variances in simulated closed herds under selection

Lino-Lourenço,Daniela Andressa; Oliveira,Carlos Antonio Lopes de; Martins,Elias Nunes; Leite,Meiby Carneiro de Paula; Maia,Fabiana Martins Costa; Santos,Alexandra Inês dos
Fonte: Editora da Universidade Estadual de Maringá - EDUEM Publicador: Editora da Universidade Estadual de Maringá - EDUEM
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/03/2012 EN
Relevância na Pesquisa
46.21%
Assuming that selection in closed herds can promote reduction in additive genetic variance, multiple regression models were used to estimate this change in additive genetic (co)variance component, over the years when the selection was done. Weights at 550 days (W550) were studied using simulated data of herds submitted to 20 years of selection. (Co)variance components were estimated assuming that the weight at 550 days was a new trait every five years, by multiple-trait analyses involving four traits in the animal model. Three multiple regression equations were fitted-RMI, RMM, RMF-estimating thus the additive genetic (co)variance components for the 20 years of selection and eight years prior to the selection process. The initial years of each generation of selection were used as a covariate in the RMI. In the RMM, intermediate years were used, and the final years were considered in the RMF. The equations showed high coefficients of determination. However, there was no difference in the adjustment between the models. It was observed that the multiple regression models can be used in the estimation of genetic (co)variance components, when heteroscedasticity is assumed over time due to the selection process.

Estimation of Variance Components of Quantitative Traits in Inbred Populations

Abney, Mark; McPeek, Mary Sara; Ober, Carole
Fonte: The American Society of Human Genetics Publicador: The American Society of Human Genetics
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
46.29%
Use of variance-component estimation for mapping of quantitative-trait loci in humans is a subject of great current interest. When only trait values, not genotypic information, are considered, variance-component estimation can also be used to estimate heritability of a quantitative trait. Inbred pedigrees present special challenges for variance-component estimation. First, there are more variance components to be estimated in the inbred case, even for a relatively simple model including additive, dominance, and environmental effects. Second, more identity coefficients need to be calculated from an inbred pedigree in order to perform the estimation, and these are computationally more difficult to obtain in the inbred than in the outbred case. As a result, inbreeding effects have generally been ignored in practice. We describe here the calculation of identity coefficients and estimation of variance components of quantitative traits in large inbred pedigrees, using the example of HDL in the Hutterites. We use a multivariate normal model for the genetic effects, extending the central-limit theorem of Lange to allow for both inbreeding and dominance under the assumptions of our variance-component model. We use simulated examples to give an indication of under what conditions one has the power to detect the additional variance components and to examine their impact on variance-component estimation. We discuss the implications for mapping and heritability estimation by use of variance components in inbred populations.

Estimation of Variance Components in the Mixed-Effects Models: A Comparison Between Analysis of Variance and Spectral Decomposition

Wu, Mi-Xia; Yu, Kai-Fun; Liu, Ai-Yi
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 01/12/2009 EN
Relevância na Pesquisa
46.21%
The mixed-effects models with two variance components are often used to analyze longitudinal data. For these models, we compare two approaches to estimating the variance components, the analysis of variance approach and the spectral decomposition approach. We establish a necessary and sufficient condition for the two approaches to yield identical estimates, and some sufficient conditions for the superiority of one approach over the other, under the mean squared error criterion. Applications of the methods to circular models and longitudinal data are discussed. Furthermore, simulation results indicate that better estimates of variance components do not necessarily imply higher power of the tests or shorter confidence intervals.

Variance Components in Discrete Force Production Tasks

SKM, Varadhan; Zatsiorsky, Vladimir M.; Latash, Mark L.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
46.28%
The study addresses the relationships between task parameters and two components of variance, “good” and “bad”, during multi-finger accurate force production. The variance components are defined in the space of commands to the fingers (finger modes) and refer to variance that does (“bad”) and does not (“good”) affect total force. Based on an earlier study of cyclic force production, we hypothesized that speeding-up an accurate force production task would be accompanied by a drop in the regression coefficient linking the “bad” variance and force rate such that variance of the total force remains largely unaffected. We also explored changes in parameters of anticipatory synergy adjustments with speeding-up the task. The subjects produced accurate ramps of total force over different times and in different directions (force-up and force-down) while pressing with the four fingers of the right hand on individual force sensors. The two variance components were quantified, and their normalized difference was used as an index of a total force stabilizing synergy. “Good” variance scaled linearly with force magnitude and did not depend on force rate. “Bad” variance scaled linearly with force rate within each task, and the scaling coefficient did not change across tasks with different ramp times. As a result...

Estimating and Testing Variance Components in a Multi-level GLM

Lindquist, Martin A.; Spicer, Julie; Asllani, Iris; Wager, Tor D.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
46.21%
Most analysis of multi-subject fMRI data is concerned with determining whether there exists a significant population-wide ‘activation’ in a comparison between two or more conditions. This is typically assessed by testing the average value of a contrast of parameter estimates (COPE) against zero in a general linear model (GLM) analysis. However, important information can also be obtained by testing whether there exist significant individual differences in effect magnitude between subjects, i.e. whether the variance of a COPE is significantly different from zero. Intuitively, such a test amounts to testing whether inter-individual differences are larger than would be expected given the within-subject error variance. We compare several methods for estimating variance components, including a) a naïve estimate using ordinary least squares (OLS); b) linear mixed effects in R (LMER); c) a novel Matlab implementation of iterative generalized least squares (IGLS) and its restricted maximum likelihood variant (RIGLS). All methods produced reasonable estimates of within- and between-subject variance components, with IGLS providing an attractive balance between sensitivity and appropriate control of false positives. Finally, we use the IGLS method to estimate inter-subject variance in a perfusion fMRI study (N = 18) of social evaluative threat...

Application of variance components estimation to calibrate geoid error models

Guo, Dong-Mei; Xu, Hou-Ze
Fonte: Springer International Publishing Publicador: Springer International Publishing
Tipo: Artigo de Revista Científica
Publicado em 20/08/2015 EN
Relevância na Pesquisa
46.21%
The method of using Global Positioning System-leveling data to obtain orthometric heights has been well studied. A simple formulation for the weighted least squares problem has been presented in an earlier work. This formulation allows one directly employing the errors-in-variables models which completely descript the covariance matrices of the observables. However, an important question that what accuracy level can be achieved has not yet to be satisfactorily solved by this traditional formulation. One of the main reasons for this is the incorrectness of the stochastic models in the adjustment, which in turn allows improving the stochastic models of measurement noises. Therefore the issue of determining the stochastic modeling of observables in the combined adjustment with heterogeneous height types will be a main focus point in this paper. Firstly, the well-known method of variance component estimation is employed to calibrate the errors of heterogeneous height data in a combined least square adjustment of ellipsoidal, orthometric and gravimetric geoid. Specifically, the iterative algorithms of minimum norm quadratic unbiased estimation are used to estimate the variance components for each of heterogeneous observations. Secondly...

Likelihood inference for small variance components

Stern, Steven E; Welsh, A. H
Fonte: Universidade Nacional da Austrália Publicador: Universidade Nacional da Austrália
Tipo: Working/Technical Paper Formato: 206647 bytes; application/pdf
EN_AU
Relevância na Pesquisa
56.18%
The authors explore likelihood-based methods for making inferences about the components of variance in a general normal mixed linear model. In particular, they use local asymptotic approximations to construct confidence intervals for the components of variance when the components are close to the boundary of the parameter space. In the process, they explore the question of how to profile the restricted likelihood (REML). Also, they show that general REML estimates are less likely to fall on the boundary of the parameter space than maximum likelihood estimates and that the likelihood ratio test based on the local asymptotic approximation has higher power than the likelihood ratio test based on the usual chi-squared approximation. They examine the finite sample properties of the proposed intervals by means of a simulation study.; no

Robust Henderson III estimators of variance components in the nested error model

Pérez, Betsabé; Peña, Daniel; Molina, Isabel
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: info:eu-repo/semantics/draft; info:eu-repo/semantics/workingPaper Formato: application/pdf
Publicado em /12/2011 ENG
Relevância na Pesquisa
56.16%
Common methods for estimating variance components in Linear Mixed Models include Maximum Likelihood (ML) and Restricted Maximum Likelihood (REML). These methods are based on the strong assumption of multivariate normal distribution and it is well know that they are very sensitive to outlying observations with respect to any of the random components. Several robust altematives of these methods have been proposed (e.g. Fellner 1986, Richardson and Welsh 1995). In this work we present several robust alternatives based on the Henderson method III which do not rely on the normality assumption and provide explicit solutions for the variance components estimators. These estimators can later be used to derive robust estimators of regression coefficients. Finally, we describe an application of this procedure to small area estimation, in which the main target is the estimation of the means of areas or domains when the within-area sample sizes are small.

Female fertility in a Guzerat dairy subpopulation: Heterogeneity of variance components for calving intervals

Panetto, J. C. C.; Val, J. E.; Marcondes, C. R.; Peixoto, M. G. C. D.; Verneque, R. S.; Ferraz, J. B. S.; Golden, B. L.
Fonte: ELSEVIER SCIENCE BV; AMSTERDAM Publicador: ELSEVIER SCIENCE BV; AMSTERDAM
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
56.15%
The objectives of the present study were to determine if variance components of calving intervals varied with age at calving and if considering calving intervals as a longitudinal trait would be a useful approach for fertility analysis of Zebu dairy herds. With these purposes, calving records from females born from 1940 to 2006 in a Guzerat dairy subpopulation in Brazil were analyzed. The fixed effects of contemporary groups, formed by year and farm at birth or at calving, and the regressions of age at calving, equivalent inbreeding coefficient and day of the year on the studied traits were considered in the statistical models. In one approach, calving intervals (Cl) were analyzed as a single trait, by fitting a statistical model on which both animal and permanent environment effects were adjusted for the effect of age at calving by random regression. In a second approach, a four-trait analysis was conducted, including age at first calving (AFC) and three different female categories for the calving intervals: first calving females; young females (less than 80 months old, but not first calving); or mature females (80 months old or more). Finally, a two-trait analysis was performed, also including AFC and Cl, but calving intervals were regarded as a single trait in a repeatability model. Additionally...