simdata function

Simulate multivariate data for testing

Simulate multivariate data for testing

Creates multivariate normal or normal and binary data, as used in the simulation study.

simdata(n = 2000, mymean = rep(0, 4), mysigma = matrix( c( 1, 0.2, 0.1, -0.7, 0.2, 1, 0.3, 0.1, 0.1, 0.3, 1, 0.2, -0.7, 0.1, 0.2, 1), byrow = TRUE, nrow = 4, ncol = 4), residsd = 1, x2binary = FALSE)

Arguments

  • n: number of observations to create.
  • mymean: vector of length 4, giving the mean of each variable.
  • mysigma: variance-covariance matrix of multivariate normal distribution from which x1-x4 are to be drawn.
  • residsd: residual standard deviation.
  • x2binary: if TRUE, x2 is converted to a binary factor variable (1, 2) with probability equal to the logistic of the underlying normally distributed variable.

Returns

Data frame with 5 columns:

  • y: continuous, generated by y = x1 + x2 + x3 + normal error if x2 is continuous, or y = x1 + x2 + x3 - 1 + normal error if x2 is a factor with values 1 or 2

  • x1: continuous

  • x2: continuous or binary (factor) with value 1 or 2

  • x3: continuous

  • x4: continuous

See Also

makemar

Examples

set.seed(1) simdata(n=4, x2binary=TRUE) # y x1 x2 x3 x4 # 1 -0.06399616 -1.23307320 2 -0.6521442 1.6141842 # 2 1.00822173 -0.05167026 1 0.4659907 0.5421826 # 3 2.87886825 0.43816687 1 1.5217240 0.2808691 # 4 0.79129101 -0.72510640 1 0.7342611 0.1820001
  • Maintainer: Anoop Shah
  • License: GPL-3
  • Last published: 2022-12-04

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