kinsim_internal: Simulate Kinship-Based Biometrically Informed Univariate Data
In discord: Functions for Discordant Kinship Modeling

kinsim_internal

R Documentation

Simulate Kinship-Based Biometrically Informed Univariate Data

Description

Generates paired univariate data for kinship pairs with specified genetic relatedness, following the classical ACE model (Additive genetic, Common environment, unique Environment).

Usage

kinsim_internal(
  r = c(1, 0.5),
  c_rel = 1,
  npg = 100,
  npergroup = rep(npg, length(r)),
  mu = 0,
  ace = c(1, 1, 1),
  r_vector = NULL,
  c_vector = NULL,
  ...
)

Arguments

`r`	Numeric vector. Levels of genetic relatedness for each group; default is c(1, 0.5) representing MZ and DZ twins respectively.
`npg`	Integer. Default sample size per group; default is 100.
`npergroup`	Numeric vector. List of sample sizes by group; default repeats `npg` for all groups in `r`.
`mu`	Numeric. Mean value for the generated variable; default is 0.
`ace`	Numeric vector. Variance components in order c(a, c, e) where a = additive genetic, c = shared environment, e = non-shared environment; default is c(1, 1, 1).
`r_vector`	Numeric vector. Alternative specification method providing relatedness coefficients for the entire sample; default is NULL.
`...`	Additional arguments passed to other methods.

Details

This function simulates data according to the ACE model, where phenotypic variance is decomposed into additive genetic (A), shared environmental (C), and non-shared environmental (E) components. It can generate data for multiple kinship groups with different levels of genetic relatedness (e.g., MZ twins, DZ twins, siblings).