mediation_analysis {exploratory}

Mediation analysis

Description

Conducts a mediation analysis to estimate an independent variable's indirect effect on dependent variable through a mediator variable. The current version of the package only supports a simple mediation model consisting of one independent variable, one mediator variable, and one dependent variable. Uses the source code from 'mediation' package v4.5.0, Tingley et al. (2019) https://cran.r-project.org/package=mediation

Usage

mediation_analysis(
  data = NULL,
  iv_name = NULL,
  mediator_name = NULL,
  dv_name = NULL,
  covariates_names = NULL,
  robust_se = TRUE,
  iterations = 1000,
  sigfigs = 3,
  output_type = "summary_dt",
  silent = FALSE
)

Arguments

data

a data object (a data frame or a data.table)

iv_name

name of the independent variable

mediator_name

name of the mediator variable

dv_name

name of the dependent variable

covariates_names

names of covariates to control for

robust_se

if TRUE, heteroskedasticity-consistent standard errors will be used in quasi-Bayesian simulations. By default, it will be set as FALSE if nonparametric bootstrap is used and as TRUE if quasi-Bayesian approximation is used.

iterations

number of bootstrap samples. The default is set at 1000, but consider increasing the number of samples to 5000, 10000, or an even larger number, if slower handling time is not an issue.

sigfigs

number of significant digits to round to

output_type

if output_type = "summary_dt", return the summary data.table; if output_type = "mediate_output", return the output from the mediate function in the 'mediate' package; if output_type = "indirect_effect_p", return the p value associated with the indirect effect estimated in the mediation model (default = "summary_dt")

silent

if silent = FALSE, mediation analysis summary, estimation method, sample size, and number of simulations will be printed; if silent = TRUE, nothing will be printed. (default = FALSE)

Value

if output_type = "summary_dt", which is the default, the output will be a data.table showing a summary of mediation analysis results; if output_type = "mediate_output", the output will be the output from the mediate function in the 'mediate' package; if output_type = "indirect_effect_p", the output will be the p-value associated with the indirect effect estimated in the mediation model (a numeric vector of length one).

Examples

mediation_analysis(
  data = mtcars, iv_name = "cyl",
  mediator_name = "disp", dv_name = "mpg", iterations = 100
)
mediation_analysis(
  data = iris, iv_name = "Sepal.Length",
  mediator_name = "Sepal.Width", dv_name = "Petal.Length",
  iterations = 100
)