mediation: Mediation analysis A Monte Carlo simulation method to assess...

In jasonmoy28/psycModel: Integrated Toolkit for Psychological Analysis and Modeling in R

Mediation analysis A Monte Carlo simulation method to assess mediation based on Selig & Preacher (2008).

Description

Mediation analysis A Monte Carlo simulation method to assess mediation based on Selig & Preacher (2008).

Usage

mediation(
  model_med,
  model_y,
  model_med2 = NULL,
  x,
  med,
  med2 = NULL,
  mod = NULL,
  mod_stage = NULL,
  mod_level = NULL,
  conf = 95,
  rep = 20000,
  verbose = TRUE,
  digits = 3
)

Arguments

model_med	a fitted model object for mediator.
model_y	a fitted model object for outcome
model_med2	a fitted model object for the second mediator for serial mediation
x	a character string indicating the name of the independent variable used in the models.
med	a character string indicating the name of the mediator used in the models.
med2	a character string indicating the name of the second mediator used in the models (for serial mediations)
mod	a character string indicating the name of the moderator used in the models.
mod_stage	a character string specifying the stage at which the moderating effect occurs. For instance, in a first-stage moderated mediation, where the moderator influences the effect of X on the mediator (Med), set this to "model_med". In a second-stage moderated mediation, where the moderator affects the relationship between the mediator (Med) and the outcome variable (Y), set this to "model_y".#'
mod_level	The default is -1 SD and +1 SD for a continuous variable, and it is the two levels for a binary variable.
conf	level of the returned two-sided confidence intervals. Default is to return the 2.5 and 97.5 percentiles of the simulated quantities (i.e., 95%).
rep	number of Monte Carlo draws
verbose	deafult is TRUE.
digits	number of digits to round to

Value

Nothing to return. Print the indirect effect.

References

Selig, J. P., & Preacher, K. J. (2008, June). Monte Carlo method for assessing mediation: An interactive tool for creating confidence intervals for indirect effects. http://quantpsy.org/.

Examples

new_dat = iris %>% 
  dplyr::rename(x = Petal.Length) %>% 
  dplyr::rename(m = Sepal.Length) %>% 
  dplyr::rename(moderator = Sepal.Width) %>% 
  dplyr::rename(y = Petal.Width)

model_1 = lm(data = new_dat, m ~ x)
model_2 = lm(data = new_dat, y ~ x*moderator + m)


mediation(model_med = model_1,
          model_y = model_2,
          rep = 20000,
          x = 'x', 
          med = 'm',
          mod = 'moderator',
          mod_stage = 'model_y',
          digits = 3)
          

jasonmoy28/psycModel documentation built on Sept. 6, 2024, 11:45 a.m.