𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A note on genetic variance components in mixed models

✍ Scribed by Martin L. Hazelton; Lyle C. Gurrin

Publisher
John Wiley and Sons
Year
2003
Tongue
English
Weight
94 KB
Volume
24
Category
Article
ISSN
0741-0395

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

Burton et al. ([1999] Genet. Epidemiol. 17:118–140) proposed a series of generalized linear mixed models for pedigree data that account for residual correlation between related individuals. These models may be fitted using Markov chain Monte Carlo methods, but the posterior mean for small variance components can exhibit marked positive bias. Burton et al. ([1999] Genet. Epidemiol. 17:118–140) suggested that this problem could be overcome by allowing the variance components to take negative values. We examine this idea in depth, and show that it can be interpreted as a computational device for locating the posterior mode without necessarily implying that the original random effects structure is incorrect. We illustrate the application of this technique to mixed models for familial data. Genet Epidemiol 24:297–301, 2003. Β© 2003 Wiley‐Liss, Inc.

πŸ“œ SIMILAR VOLUMES

Estimation of Variance Components in Mix
Estimation of Variance Components in Mixed Linear Models
✍ T. Kubokawa πŸ“‚ Article πŸ“… 1995 πŸ› Elsevier Science 🌐 English βš– 775 KB

In mixed linear models with two variance components, classes of estimators improving on ANOVA estimators for the variance components and the ratio of variances are constructed on the basis of the invariant statistics. Out of the classes, consistent, improved and positive estimators are singled out.

On the Optimality of F-test on Variance
On the Optimality of F-test on Variance Components in Mixed Linear Models
✍ Dr. P. Roebruck πŸ“‚ Article πŸ“… 1982 πŸ› John Wiley and Sons 🌐 English βš– 223 KB πŸ‘ 3 views

## Abstract The analysis‐of‐variance tests for hypotheses on random effects in regular linear models are considered. Conditions are given for these tests to be uniformly most powerful unbiased or uniformly most powerful invariant unbiased. An example shows that the difference between these conditio

Bootstrap tests for variance components
Bootstrap tests for variance components in generalized linear mixed models
✍ Sanjoy K. Sinha πŸ“‚ Article πŸ“… 2009 πŸ› John Wiley and Sons 🌐 French βš– 141 KB πŸ‘ 3 views

## Abstract In many applications of generalized linear mixed models to clustered correlated or longitudinal data, often we are interested in testing whether a random effects variance component is zero. The usual asymptotic mixture of chi‐square distributions of the score statistic for testing const

Improved Nonnegative Estimation of Varia
Improved Nonnegative Estimation of Variance Components in Balanced Multivariate Mixed Models
✍ T. Mathew; A. Niyogi; B.K. Sinha πŸ“‚ Article πŸ“… 1994 πŸ› Elsevier Science 🌐 English βš– 704 KB

Consider the independent Wishart matrices \(S_{1} \sim W\left(\Sigma+\lambda \theta, q_{1}\right)\) and \(S_{2} \sim\) \(W\left(\Sigma, q_{2}\right)\), where \(\Sigma\) is an unknown positive definite (p.d.) matrix, \(\theta\) is an unknown nonnegative definite (n.n.d.) matrix, and \(\lambda\) is a