GRE: This function implement the generalized random effects model...

In hychen-uic/TEV: Total Explained Variation

This function implement the generalized random effects model approach.

Description

This function uses least-square estimates in computing the proportion of the explained variation. It is simply just the least-square approach to estimate heritability.The general GRE assumes covariates are blockwise independent. This function can be applied to one block. Variance estimate is good for normal outcome only.

Usage

GRE(y, x, alpha = c(0.05))

Arguments

y	outcome: a vector of length n.
x	covariates: a matrix of nxp dimension.
alpha	a vector of type I errors used to generate (1-alpha)confidence intervals.

Details

This method works only for the case n>p. It uses the least-square approach for the estimation. Covariates are allowed to be correlated.

Value

Estimate of proportion of the explained variation, variance estimates, and the corresponding confidence intervals.

References

Hou et al (2019). Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture. NAture GeNeticS, 51, 1244–1251.

Examples

## Not run: GRE(y,x)

hychen-uic/TEV documentation built on Jan. 24, 2025, 9:14 p.m.