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
).
See also
Other simulation:
complement()
,
simulateAUC()