gendat_med_simple: Generate Simple Mediation Model Data

In jeksterslabds/jeksterslabRds: Jekster's Lab Data Science and Statistics

Description

Generates data from a simple mediation model.

Usage

gendat_med_simple(
  n,
  alpha,
  tau_prime,
  beta,
  delta_M,
  delta_Y,
  sigma2_epsilon_M,
  sigma2_epsilon_Y,
  rFUN_X,
  ...
)

Arguments

n	Sample size.
alpha	Path from X to M (α).
tau_prime	Path from X to Y (τ^{\prime}).
beta	Path from M to Y (β).
delta_M	Intercept for the first equation (δ_M).
delta_Y	Intercept for the second equation (δ_Y).
sigma2_epsilon_M	Variance of ε_M (σ^{2}_{ε_{M}}).
sigma2_epsilon_Y	Variance of ε_Y (σ^{2}_{ε_{Y}}).
rFUN_X	The distribution function used to generate values of \mathbf{X}. The default value is rnorm for the Gaussian probability density function.
...	Arguments to pass to rFUN_X.

Details

The simple mediation model is defined by M_i = δ_M + α X_i + ε_{M_i}, and Y_i = δ_Y + τ^{\prime} X_i + β M_i + ε_{Y_i}. X is generated using distribution supplied by rFUN_X (rnorm is the default). Additional arguments to rFUN_X are supplied using the ... argument. M and Y are generated using X and the parameters provided using the regression equations above. Residuals are assumed to be normaly distribution with means of zero and provided variances σ^{2}_{ε_{M}} and σ^{2}_{ε_{Y}}.

Examples

data <- gendat_med_simple(
  n = 100,
  alpha = 0.26^(1 / 2),
  tau_prime = 0,
  beta = 0.26^(1 / 2),
  delta_M = 0.490098,
  delta_Y = 0.490098,
  sigma2_epsilon_M = 0.74,
  sigma2_epsilon_Y = 0.74,
  rFUN_X = rnorm,
  mean = 0,
  sd = 1
)

jeksterslabds/jeksterslabRds documentation built on July 16, 2020, 3:41 p.m.