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Simulate indirect effect from mediation analyses.

Usage

simulateIndirectEffect(
  N = NA,
  x = NA,
  m = NA,
  XcorM = NA,
  McorY = NA,
  corTotal = NA,
  proportionMediated = NA,
  seed = NA
)

Arguments

N

Sample size.

x

Vector for the predictor variable.

m

Vector for the mediating variable.

XcorM

Coefficient of the correlation between the predictor variable and mediating variable.

McorY

Coefficient of the correlation between the mediating variable and outcome variable.

corTotal

Size of total effect.

proportionMediated

The proportion of the total effect that is mediated.

seed

Seed for replicability.

Value

  • the correlation between the predictor variable (x) and the mediating variable (m).

  • the correlation between the mediating variable (m) and the outcome variable (Y).

  • the correlation between the predictor variable (x) and the outcome variable (Y).

  • the direct correlation between the predictor variable (x) and the outcome variable (Y), while controlling for the mediating variable (m).

  • the indirect correlation between the predictor variable (x) and the outcome variable (Y) through the mediating variable (m).

  • the total correlation between the predictor variable (x) and the outcome variable (Y): i.e., the sum of the direct correlation and the indirect correlation.

  • the proportion of the correlation between the predictor variable (x) and the outcome variable (Y) that is mediated through the mediating variable (m).

Details

Co-created by Robert G. Moulder Jr. and Isaac T. Petersen

See also

Other simulation: complement(), simulateAUC()

Examples

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Developmental Psychopathology Lab