Title:	Statistical Mediation Analysis for SEMs
Version:	1.0.0
Description:	Conducts mediation analysis for structural equation models (SEM) estimated with 'lavaan', 'blavaan', 'cSEM', or 'modsem'. Implements the Baron and Kenny (1986) <doi:10.1037/0022-3514.51.6.1173> and Zhao, Lynch & Chen (2010) <doi:10.1086/651257> approaches to determine the presence and type of mediation. Supports covariance-based SEM, partial least squares SEM, Bayesian SEM, and moderated mediation models. Reports indirect effects with standard errors from Sobel, Delta, Monte-Carlo, and bootstrap methods, along with effect size measures (RIT, RID).
License:	MIT + file LICENSE
Encoding:	UTF-8
RoxygenNote:	7.3.2
Imports:	lavaan, mvtnorm, ggplot2, dplyr, purrr, stats
URL:	https://github.com/ihrke/rmedsem, https://ihrke.github.io/rmedsem/
BugReports:	https://github.com/ihrke/rmedsem/issues
Depends:	R (≥ 4.1.0)
LazyData:	true
Suggests:	blavaan, boot, cSEM, HDInterval, modsem, semPlot, rmarkdown, testthat (≥ 3.0.0)
Config/testthat/edition:	3
NeedsCompilation:	no
Packaged:	2026-03-10 21:13:16 UTC; mmi041
Author:	Mehmet Mehmetoglu [aut], Matthias Mittner [aut, cre], Kjell Slupphaug [aut]
Maintainer:	Matthias Mittner <matthias.mittner@uit.no>
Repository:	CRAN
Date/Publication:	2026-03-16 16:50:02 UTC

Ratio of Indirect to Direct Effect (RID)

Description

Ratio of Indirect to Direct Effect (RID)

Usage

RID(res, ...)

## S3 method for class 'rmedsem'
RID(res, ...)

Arguments

Value

A numeric scalar giving the ratio of the indirect effect to the direct effect (indirect / direct).

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science")
RID(out)

Ratio of Indirect to Total Effect (RIT)

Description

Ratio of Indirect to Total Effect (RIT)

Usage

RIT(res, ...)

## S3 method for class 'rmedsem'
RIT(res, ...)

Arguments

Value

A numeric scalar giving the ratio of the indirect effect to the total effect (indirect / total).

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science")
RIT(out)

Upsilon Effect Size

Description

Returns the Upsilon effect size (Lachowicz, Preacher & Kelley, 2018), an R-squared-type measure representing the variance in Y explained indirectly by X through M.

Usage

Upsilon(res, ...)

## S3 method for class 'rmedsem'
Upsilon(res, adjusted = TRUE, ...)

Arguments

Value

A numeric scalar giving the Upsilon effect size, an R-squared-type measure of the variance in the dependent variable explained indirectly through the mediator.

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science",
               effect.size=c("RIT","RID","upsilon"))
Upsilon(out)
Upsilon(out, adjusted=FALSE)

Convert an rmedsem Object to a Data Frame

Description

Convert an rmedsem Object to a Data Frame

Usage

## S3 method for class 'rmedsem'
as.data.frame(x, ...)

Arguments

Value

a data.frame

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science")
as.data.frame(out)

High School and Beyond Demo Dataset

Description

High School and Beyond Demo Dataset

Usage

hsbdemo

Format

hsbdemo

A data frame with 20 rows and 13 columns:

id

Student ID

female

Mate-Choice Survey Data from Trondheim

Description

Data from a survey on mate-choice in Trondheim.

Usage

mchoice

Format

mchoice

A data frame with 1090 rows and 9 columns:

smv_attr_face

How well does this describe you as a partner?, [1] very bad - [5] very well

smv_attr_body

How well does this describe you as a partner?, [1] very bad - [5] very well

smv_sexy

How well does this describe you as a partner?, [1] very bad - [5] very well

ses_satis

On the whole, I am satisfied with myself, [1] totally disgree - [5] totally agree

ses_qualities

I feel that I have a number of good qualities, [1] totally disgree - [5] totally agree

ses_able_todo

I am able to do things as well as most other people, [1] totally disgree - [5] totally agree

mwb_optimistic

I have been feeling optimistic about the future, [1] never - [5] always

mwb_useful

I have been feeling useful, [1] never - [5] always

mwb_energy

I have had energy to spare, [1] never - [5] always

smv_kind

?, [1] ? - [5] ?

smv_caring

?, [1] ? - [5] ?

smv_understanding

?, [1] ? - [5] ?

smv_make_laughh

?, [1] ? - [5] ?

smv_funny

?, [1] ? - [5] ?

smv_sociable

?, [1] ? - [5] ?

Plot an rmedsem Object

Description

Creates a visualization of the mediation analysis results. By default, produces a coefficient plot. Use type = "effect" for an effect size pie chart.

Usage

## S3 method for class 'rmedsem'
plot(x, type = c("coef", "effect"), ...)

Arguments

Value

a ggplot object

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science")
plot(out)
plot(out, type="effect")

Plot Coefficients for an rmedsem Object

Description

Plot Coefficients for an rmedsem Object

Usage

plot_coef(res)

Arguments

Value

a ggplot object

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science")
plot_coef(out)

Plot Effect Sizes for an rmedsem Object

Description

Plot Effect Sizes for an rmedsem Object

Usage

plot_effect(res, description = TRUE)

Arguments

Value

a ggplot object

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science")
plot_effect(out)

Indent and merge strings

Description

Indent and merge strings

Usage

pre_indent_merge(s, indent)

Arguments

Value

indented string

Print an rmedsem Object

Description

Print an rmedsem Object

Usage

## S3 method for class 'rmedsem'
print(x, digits = 3, indent = 3, ...)

Arguments

Value

the rmedsem object x (invisibly)

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science")
print(out)

Print rmedsem Results for Blavaan Models

Description

Print rmedsem Results for Blavaan Models

Usage

## S3 method for class 'rmedsem.blavaan'
print(x, digits = 3, indent = 3, ...)

Arguments

Value

rmedsem object x (invisibly)

Print rmedsem Results for Lavaan, cSEM, and Modsem Models

Description

Print rmedsem Results for Lavaan, cSEM, and Modsem Models

Usage

## S3 method for class 'rmedsem.lavaan.csem.modsem'
print(x, digits = 3, indent = 3, ci_moderation = FALSE, ...)

Arguments

Value

rmedsem object x (invisibly)

Print Effect Sizes from Mediation Analysis

Description

Print Effect Sizes from Mediation Analysis

Usage

print_effectsize(res, digits = 3, indent = 3)

Arguments

Value

rmedsem object res (invisibly)

Mediation Analysis for Structural Equation Models

Description

Conducts mediation analysis on a fitted SEM model using the Baron and Kenny (1986) and/or Zhao, Lynch & Chen (2010) approaches.

Usage

rmedsem(
  mod,
  indep,
  med,
  dep,
  approach = c("bk", "zlc"),
  p.threshold = 0.05,
  effect.size = c("RIT", "RID", "upsilon"),
  ...
)

Arguments

Value

an object of class rmedsem

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science")
out

Mediation Analysis for Blavaan Models

Description

Mediation Analysis for Blavaan Models

Usage

## S3 method for class 'blavaan'
rmedsem(
  mod,
  indep,
  med,
  dep,
  approach = c("bk", "zlc"),
  p.threshold = 0.05,
  effect.size = c("RIT", "RID", "upsilon"),
  ...
)

Arguments

Value

A rmedsem structure containing the results from the analysis

Examples

## Not run: 
# Requires blavaan and a MCMC backend (Stan/JAGS)
model02 <- "
  # measurement model
    ind60 =~ x1 + x2 + x3
    dem60 =~ y1 + y2 + y3 + y4
    dem65 =~ y5 + y6 + y7 + y8
  # regressions
    dem60 ~ ind60
    dem65 ~ ind60 + dem60
"
mod <- blavaan::bsem(model02, data=lavaan::PoliticalDemocracy, std.lv=TRUE,
            meanstructure=TRUE, n.chains=1,
            save.lvs=TRUE, burnin=500, sample=500)
out <- rmedsem(mod,  indep="ind60", med="dem60", dep="dem65")
print(out)

## End(Not run)

Mediation Analysis for cSEM Models

Description

Mediation Analysis for cSEM Models

Usage

## S3 method for class 'cSEMResults'
rmedsem(
  mod,
  indep,
  med,
  dep,
  approach = c("bk", "zlc"),
  p.threshold = 0.05,
  effect.size = c("RIT", "RID", "upsilon"),
  nbootstrap = 1000,
  ci.two.tailed = 0.95,
  ...
)

Arguments

Value

A rmedsem structure containing the results from the analysis

Mediation Analysis for Lavaan Models

Description

Mediation Analysis for Lavaan Models

Usage

## S3 method for class 'lavaan'
rmedsem(
  mod,
  indep,
  med,
  dep,
  approach = c("bk", "zlc"),
  p.threshold = 0.05,
  effect.size = c("RIT", "RID", "upsilon"),
  standardized = TRUE,
  mcreps = NULL,
  ci.two.tailed = 0.95,
  ...
)

Arguments

Value

A rmedsem structure containing the results from the analysis

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science",
               standardized=TRUE, mcreps=5000,
               approach = c("bk","zlc"))
print(out)

Mediation Analysis for Modsem Models

Description

Mediation Analysis for Modsem Models

Usage

## S3 method for class 'modsem'
rmedsem(
  mod,
  indep,
  med,
  dep,
  approach = c("bk", "zlc"),
  p.threshold = 0.05,
  effect.size = c("RIT", "RID", "upsilon"),
  moderator = NULL,
  standardized = TRUE,
  mcreps = NULL,
  ci.two.tailed = 0.95,
  ...
)

Arguments

Value

A rmedsem structure containing the results from the analysis

Examples

if (requireNamespace("modsem", quietly = TRUE)) {
  m <- "
    OwnLook =~ smv_attr_face + smv_attr_body + smv_sexy
    SelfEst =~ ses_satis + ses_qualities + ses_able_todo
    MentWell =~ mwb_optimistic + mwb_useful + mwb_energy
    smv =~ smv_kind + smv_caring + smv_understanding +
      smv_make_laughh + smv_funny + smv_sociable
    SelfEst ~ OwnLook + smv + smv:OwnLook
    MentWell ~ OwnLook + SelfEst + smv + smv:OwnLook
  "

  est <- modsem::modsem(m, data = mchoice, method="lms")

  # mediated moderation
  rmedsem(indep="smv:OwnLook", dep="MentWell", med="SelfEst", mod=est)

  # moderated mediation
  rmedsem(indep="OwnLook", dep="MentWell", med="SelfEst", mod=est, moderator="smv")
}

Summarize an rmedsem Object

Description

Prints the mediation analysis results to the console.

Usage

## S3 method for class 'rmedsem'
summary(object, ...)

Arguments

Value

the rmedsem object (invisibly)

Examples

mod.txt <- "
read ~ math
science ~ read + math
"
mod <- lavaan::sem(mod.txt, data=rmedsem::hsbdemo)
out <- rmedsem(mod, indep="math", med="read", dep="science")
summary(out)

Validate common rmedsem arguments

Description

Validate common rmedsem arguments

Usage

validate_rmedsem_args(indep, med, dep, approach, p.threshold, effect.size)

Fitness Center Survey Data from Trondheim

Description

Data from a survey in a fitness center in Trondheim.

Usage

workout

Format

workout

A data frame with 246 rows and 12 columns:

age

Age in years

lweight

How important is following to workout- to loose weight

calories

How important is following to workout- to burn calories

cweight

How important is following to workout- to control my weight

body

How important is following to workout- to have a good body

appear

How important is following to workout- to improve my appearance

attract

How important is following to workout- to look more attractive

muscle

How important is following to workout- to develop my muscles

strength

How important is following to workout- to get stronger

endur

How important is following to workout- to increase my endurance

face

How well does the following describe you as a person - attractive face

sexy

How well does the following describe you as a person - sexy