Recent work by Reiss and Ogden (2009) provides a theoretical basis for sometimes preferring restricted maximum likelihood (REML) to generalized cross validation (GCV) for smoothing parameter selection in semiparametric regression. However, existing REML or marginal likelihood (ML) based methods for semiparametric GLMs use iterative REML/ML estimation of the smoothing parameters of working linea...

Resumen Background: Likelihood-based methods can work poorly when the residuals are not normally distributed and the variances across clusters are heterogeneous. Method: The performance of two estimation methods, the non-parametric residual bootstrap (RB) and the restricted maximum likelihood (REML) for fi tting multilevel models are compared through simulation studies in terms of bias, coverag...

Performance of the "quasi-REML" method for estimating correlations between a continuous trait and a categorical trait, and between two categorical traits, was studied with Monte Carlo simulations. Three continuous, correlated traits were simulated for identical populations and three scenarios with either no selection, selection for one moderately heritable trait (Trait 1, h2 = .25), and selecti...

Intensive selection of broilers for improved growth rate is known to exert a negative effect on broiler health, such as an increase in body fat (and its related diseases). Excessive fat deposition in the liver can cause fatty liver hemorrhagic syndrome (FLHS); in addition, traits associated with liver fat have also been associated with FLHS. This study explored the genetic relationships among l...

Estimates of heritability within herd (h(WH)(2) ) that were generated with daughter-dam regression, daughter-sire regression, and REML were compared, and effects of adjusting lactation records for within-herd heritability on genetic evaluations were evaluated. Holstein records for milk, fat, and protein yields and somatic cell score (SCS) from the USDA national database represented herds in the...

Method R and Restricted Maximum Likelihood (REML) were compared for estimating heritability (h2) and subsequent prediction of breeding values (a) with data subject to selection. A single-trait animal model was used to generate the data and to predict breeding values. The data originated from 10 sires and 100 dams and simulation progressed for 10 overlapping generations. In simulating the data, ...

The application of the concentration ratio (CR) to predict radionuclide activity concentrations in wildlife from those in soil or water has become the widely accepted approach for environmental assessments. Recently both the ICRP and IAEA have produced compilations of CR values for application in environmental assessment. However, the CR approach has many limitations, most notably, that the tra...

Nonlinear mixed effects models are now widely used in biometrical studies, especially in pharmacokinetic research or for the analysis of growth traits for agricultural and laboratory species. Most of these studies, however, are often based on ML estimation procedures, which are known to be biased downwards. A few REML extensions have been proposed, but only for approximated methods. The aim of ...

Regions in the genome that affect complex traits, quantitative trait loci (QTL), can be identified using statistical analysis of genetic and phenotypic data. When restricted maximum-likelihood (REML) models are used, the mapping procedure is normally computationally demanding. We develop a new efficient computational scheme for QTL mapping using variance component analysis and the AI-REML algor...

BIJMA et al. (2007a,b) presented a quantitative genetic theory of multilevel selection and showed how to estimate the relevant parameters using standard REML methodology. Extending their results we develop a wider class of models that provide a more realistic framework for capturing the effects of interacting individuals. These models also make use of standard REML techniques, and include the o...