Confidence Intervals for Ratios of Linear Functions of Mixed Models with Reference to Animal Breeding Data

1980 ◽  
Vol 50 (6) ◽  
pp. 1051-1056 ◽  
Author(s):  
Daniel Gianola
Keyword(s):  
Confidence Intervals ◽  
Mixed Models ◽  
Animal Breeding ◽  
Linear Functions

scholarly journals Software update: Moving the R package sommer to multivariate mixed models for genome-assisted prediction

2018 ◽  
Author(s):  
Giovanny Covarrubias-Pazaran
Keyword(s):  
Random Effects ◽  
Mixed Models ◽  
Mixed Model ◽  
R Package ◽  
Animal Breeding ◽  
Breeding Programs ◽  
Incidence Matrices ◽  
Software Update ◽  
Trial Analysis ◽  
User Friendly

AbstractIn the last decade the use of mixed models has become a pivotal part in the implementation of genome-assisted prediction in plant and animal breeding programs. Exploiting the use genetic correlation among traits through multivariate predictions has been proposed in recent years as a way to boost prediction accuracy and understand pleiotropy and other genetic and ecological phenomena better. Multiple mixed model solvers able to use relationship matrices or deal with marker-based incidence matrices have been released in the last years but multivariate versions are scarse. Such solvers have become quite popular in plant and animal breeding thanks to user-friendly platforms such as R. Among such software one of the most recent and popular is the sommer package. In this short communication we discuss the update of the package that is able to run multivariate mixed models with multiple random effects and different covariance structures at the level of random effects and trait-to-trait covariance along with other functionalities for genetic analysis and field trial analysis to enhance the genome-assisted prediction capabilities of researchers.

scholarly journals Bayes factor between Student t and Gaussian mixed models within an animal breeding context

2008 ◽  
Vol 40 (4) ◽  
pp. 395 ◽  
Author(s):  
Joaquim Casellas ◽  
Noelia Ibáñez-Escriche ◽  
Luis García-Cortés ◽  
Luis Varona
Keyword(s):  
Mixed Models ◽  
Bayes Factor ◽  
Animal Breeding

Simultaneous Confidence Intervals for the Linear Functions of Expected Mean Squares Used in Generalizability Theory

1986 ◽  
Vol 11 (3) ◽  
pp. 197-205
Author(s):  
John F. Bell
Keyword(s):  
Linear Model ◽  
Confidence Intervals ◽  
Random Effects ◽  
Variance Components ◽  
Generalizability Theory ◽  
Linear Functions ◽  
Simultaneous Confidence Intervals ◽  
Balanced Design ◽  
Expected Values ◽  
Bonferroni's Inequality

This paper demonstrates a method, derived by Khuri (1981) , of constructing simultaneous confidence intervals for functions of expected values of mean squares obtained when analyzing a balanced design by a random effects linear model. The method may be applied to obtain confidence intervals for the variance components and other linear functions of the expected mean squares used in generalizability theory, with probability of simultaneous coverage guaranteed to be greater than or equal to the specified confidence coefficient. The Khuri intervals are compared with the approximate intervals obtained by using Satterthwaite’s (1941 , 1946) method in conjunction with Bonferroni’s inequality.

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