rSPARCS (version 0.1.1)

mediationking: Mediating Analysis

Description

This function provides convenient algorithm to calculate total effect, mediation effect, direct effect and the proportion of mediation effect.

Usage

mediationking(dataset,outcome,mediator,exposure,n.sim)

Value

Total effect

The total effect of the exposure on the outcome variable.

Indirect effect

The effect of the exposure on the outcome variable that is caused by mediator.

Direct effect

The effect of the exposure on the outcome variable that is caused by factors other than the mediator.

Meditation.proportion

The proportion of the mediation effect.

Arguments

dataset

The dataset that is used for analysis.

outcome

The name of the outcome variable in the dataset.

mediator

The name of the mediator in the dataset.

exposure

The name of the exposure factor in the dataset.

n.sim

Times of simulation to estimate 95% confidence intervals.

Details

Please use set.seed() if you want to get a consistent result; this function will be expended to allow more covariates shortly.

Examples

set.seed(1)
exposure<-rnorm(20,0,1)
mediator<-rnorm(20,10,1)
outcome<-rnorm(20,10,1)
dataset<-data.frame(outcome,mediator,exposure)
mediationking(dataset,"outcome","mediator","exposure")