fit.large: Prefitted model: large data set

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

Description

A large quad-variate data set was simulated assuming an underlying Cholesky model, with 5000 observations per trait and high polygenicity (20,000 SNPs per genetic factor). Genetic trait variances were set to 0.30, 0.60, 0.60 and 0.70 respectively, and residual variances to 0.70, 0.40, 0.40 and 0.30. The data set is described in full, including genetic and residual covariances, in the vignette. A 4-variate Cholesky model was fitted to the data as described in the vignette and the output has been saved in fit.large.RData.

Usage

fit.large

Format

gsem.fit output (a list object)

model.in

input parameters

formula

fitted formula

model.fit

optimisation output

model.out

fitted gsem model

VCOV

variance covariance matrix

k

Number of phenotypes

n

Number of observations across all phenotypes

n.obs

Number of observations per phenotype

n.ind

Number of individuals with at least one phenotype

model

gsem model

con

constraint

ph.nms

phenotype names

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