observLmer2: Variance components for normal data 2
Description
Extracts additive genetic, non-additive genetic, and maternal variance components
from a linear mixed-effect model using the lmer function of the lme4 package.
Model random effects are dam, sire, and dam by sire.
Options to include one random position and/or one random block effect(s).
Usage
observLmer2(observ, dam, sire, response, position = NULL, block = NULL, ml = F)
Value
A list object containing the raw variance components, the variance components as a percentage
of the total variance component. Also, contains the difference in AIC and BIC, and likelihood ratio
test Chi-square and p-value for all random effects.
Arguments
observ
Data frame of observed data.
dam
Column name containing dam (female) parent identity information.
sire
Column name containing sire (male) parent identity information.
response
Column name containing the offspring (response) phenotype values.
position
Optional column name containing position factor information.
block
Optional column name containing block factor information.
ml
Default is FALSE for restricted maximum likelihood. Change to TRUE for maximum likelihood.
Details
Extracts the dam, sire, dam, dam by sire, and residual variance components.
Extracts optional position and block variance components.
Calculates the total variance component. Calculates the additive genetic, non-additive genetic, and
maternal variance components (see Lynch and Walsh 1998, p. 603).
Significance values for the random effects are determined using likelihood ratio tests (Bolker et al. 2009).
References
Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, Stevens MHH, White J-SS. 2009.
Generalized linear mixed models: a practical guide for ecology and evolution.
Trends in Ecology and Evolution 24(3): 127-135. DOI: 10.1016/j.tree.2008.10.008
Lynch M, Walsh B. 1998. Genetics and Analysis of Quantitative Traits. Sinauer Associates, Massachusetts.