grmsem.var: grmsem variance estimation function

In grmsem: Genetic-Relationship-Matrix Structural Equation Modelling (GRMSEM)

Description

This function estimates genetic and residual variances, and genetic correlations.

Usage

grmsem.var(grmsem.out = NULL)

Arguments

grmsem.out

A grmsem.fit or grmsem.stpar object. Default NULL.

Details

The grmsem.var function can be used to estimate genetic and residual covariance and correlations for DS, Cholesky, IP and IPC models, based on grmsem.fit or grmsem.stpar objects. For the latter, the diagonal elements of the VA output matrix detail the heritabilities. Except for directly estimated variance components using the DS model, all standard errors are derived with the Delta method.

Value

grmsem.var returns a list object consisting of the following matrices:

VA	estimated genetic variance
VA.se	standard error of estimated genetic variance
VE	estimated residual variance
VE.se	standard error of estimated residual variance
VP	estimated total phenotypic variance
RG	genetic correlation
RG.se	standard error genetic correlation
RE	residual correlation
RG.se	standard error residual correlation

Examples

#(runtime should be less than one minute)

out <- grmsem.fit(ph.small, G.small, LogL = TRUE, estSE = TRUE)
var.out <- grmsem.var(out)
print(var.out)

grmsem documentation built on Jan. 29, 2021, 5:07 p.m.