sim.data.cluster: Goodness-of fit test for LMM, function to simulate data

In rokblagus/gofLMM: Goodness-of-fit for linear mixed effects model (gofLMM)

Goodness-of fit test for LMM, function to simulate data

Description

This function can be used to simulate (balanced) cluster data as used in the simulation study of Peterlin et al. See the paper for details.

Usage

sim.data.cluster(
  N,
  n,
  betas,
  norm.eps,
  var.eps = NULL,
  shape = NULL,
  scale = NULL,
  norm.re.intercept,
  var.re.intercept = NULL,
  shape.re.intercept = NULL,
  scale.re.intercept = NULL,
  sim.re.slope,
  norm.re.slope = NULL,
  var.re.slope = NULL,
  shape.re.slope = NULL,
  scale.re.slope = NULL,
  sim.x2.qdr = FALSE,
  b.qdr = NULL
)

Arguments

N	number of clusters
n	number of subjects per cluster (the same for all clusters)
betas	Vector of true regression coefficients for the fixed effects
norm.eps	Logical, if TRUE the errors are simulated from a (zero mean) normal distribution with variance var.eps, otherwise from a (centered) gama with parameters shape and scale
var.eps	see above
shape	see above
scale	see above
norm.re.intercept	Logical, if TRUE the random intercepts are simulated from a (zero mean) normal distribution with variance var.re.intercept, otherwise from a (centered) gama with parameters shape.re.intercept and scale.re.intercept
var.re.intercept	see above
shape.re.intercept	see above
scale.re.intercept	see above
sim.re.slope	Logical. If TRUE random slopes are simulated.
norm.re.slope	Logical, if TRUE the random slopes are simulated from a (zero mean) normal distribution with variance var.re.slope, otherwise from a (centered) gama with parameters shape.re.slope and scale.re.slope
var.re.slope	see above
shape.re.slope	see above
scale.re.slope	see above
sim.x2.qdr	Logical. If TRUE the square of X2 is included in the true (correct) fixed effects design matrix.
b.qdr	True beta coefficient associated with the square of X2

Author(s)

Rok Blagus, [e-mail]

See Also

gof.lmm

rokblagus/gofLMM documentation built on April 4, 2022, 8:41 p.m.