kinsim_internal: Simulate Biometrically informed Univariate Data

In discord: Functions for Discordant Kinship Modeling

Description

Generate paired univariate data, given ACE parameters.

Usage

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

Arguments

r	Levels of relatedness; default is MZ and DZ twins c(1,.5)
npg	Sample size per group; default is 100.
npergroup	List of sample sizes by group; default repeats npg for all groups.
mu	Mean for generated variable; default is 0.
ace	Vector of variance components, ordered by c(a, c, e); default is c(1,1,1).
r_vector	Alternative, give vector of relatedness coefficients for entire sample.
...	Optional pass on additional inputs.

Value

Returns data.frame with the following:

id	id
A1	genetic component for kin1
A2	genetic component for kin2
C1	shared-environmental component for kin1
C2	shared-environmental component for kin2
E1	non-shared-environmental component for kin1
E2	non-shared-environmental component for kin2
y1	generated variable for kin1 with mean of mu
y2	generated variable for kin2 with mean of mu
r	level of relatedness for the kin pair

discord documentation built on July 15, 2021, 9:06 a.m.