sim.QTL.data.GxE: Simulates subjects for continuous outcome

In kwesterman/ESPRESSO.GxE.RV: Power analysis and sample size calculation for a multi-variant gene-environment interaction model

Simulates subjects for continuous outcome

Description

Generates the specified number of subjects

Usage

sim.QTL.data.GxE(
  n = NULL,
  ph.mean = NULL,
  ph.sd = NULL,
  g.nvar = NULL,
  g.frac_causal = NULL,
  freq = NULL,
  g.model = NULL,
  g.efkt = NULL,
  e.model = NULL,
  e.efkt = NULL,
  e.prev = NULL,
  e.mean = NULL,
  e.sd = NULL,
  e.low.lim = NULL,
  e.up.lim = NULL,
  i.efkt = NULL,
  pheno.rel = NULL
)

Arguments

n	Number of subjects to simulate
ph.mean	statistical mean
ph.sd	standard deviation
g.nvar	Integer number of genetic variants to simulate
g.frac_causal	Fraction of causal genetic variants
freq	Minor allele frequencies of the genetic variants
g.model	Genetic model; 0 for binary and 1 for continuous
g.efkt	Effects of the genetic variant
e.model	Model of the environmental exposure
e.efkt	Effects of the environment determinats
e.prev	Prevalences of the environmental determinants
e.mean	Mean under quantitative-normal model
e.sd	Standard deviation under quantitative-normal model
e.low.lim	lower limit under quantitative-uniform model
e.up.lim	upper limit under quantitative-uniform model
i.efkt	Interaction effect
pheno.rel	reliability of the assessment for a quantitative outcome.

Value

A matrix

Author(s)

Gaye A.; Westerman K.

kwesterman/ESPRESSO.GxE.RV documentation built on Aug. 27, 2023, 4:44 a.m.