Package 'rmedsem' reference manual

Title:	Statistical Mediation Analysis for SEMs
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).
Authors:	Mehmet Mehmetoglu [aut] (ORCID: <https://orcid.org/0000-0002-6092-8551>), Matthias Mittner [aut, cre] (ORCID: <https://orcid.org/0000-0003-0205-7353>), Kjell Slupphaug [aut] (ORCID: <https://orcid.org/0009-0005-8324-2834>)
Maintainer:	Matthias Mittner <[email protected]>
License:	MIT + file LICENSE
Version:	1.0.0.9000
Built:	2026-05-17 05:20:56 UTC
Source:	https://github.com/ihrke/rmedsem

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

Arguments

x

the rmedsem object

...

additional arguments (currently unused)

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)

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
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
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 Coefficients for an rmedsem Object

Description

Plot Coefficients for an rmedsem Object

Usage

plot_coef(res)
plot_coef(res)

Arguments

res

the rmedsem object

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)

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)
plot_effect(res, description = TRUE)

Arguments

res

the rmedsem object

description

logical, whether to add a description subtitle

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)

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)

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

Arguments

x

the rmedsem object

type

character; either "coef" (default) for a coefficient plot or "effect" for an effect size plot

...

additional arguments passed to plot_coef() or plot_effect()

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")

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")

Print an rmedsem Object

Description

Print an rmedsem Object

Usage

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

Arguments

x

the rmedsem object to print

digits

an integer, number of digits to print in table

indent

an integer, number of spaces to indent

...

additional arguments (currently unused)

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)

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)

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, ...)
RID(res, ...)

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

Arguments

res

fitted rmedsem object

...

additional arguments (currently unused)

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)

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, ...)
RIT(res, ...)

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

Arguments

res

fitted rmedsem object

...

additional arguments (currently unused)

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)

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)

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

Arguments

mod

a fitted SEM model object (from lavaan, blavaan, cSEM, or modsem)

indep

a string indicating the name of the independent variable

med

a string indicating the name of the mediator variable

dep

a string indicating the name of the dependent variable

approach

either "bk" or "zlc" or both c("bk", "zlc") (default)

p.threshold

a numeric giving the p-value threshold for significance

effect.size

character vector; one or more of "RIT", "RID", "upsilon"

...

additional arguments passed to methods

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

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"),
  ...
)
## 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

mod

A fitted SEM model (blavaan). Note that the model has to be fit using save.lvs=TRUE if the mediation model contains latent variables.

indep

A string indicating the name of the independent variable in the model.

med

A string indicating the name of the mediator variable in the model.

dep

A string indicating the name of the dependent variable in the model.

approach

either 'bk' or 'zlc' or both c("bk", "zlc") (default)

p.threshold

A double giving the p-value for determining whether a path is significant or not

effect.size

calculate different effect-sizes; one or more of "RIT", "RID"

...

additional arguments (currently unused)

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)
## 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,
  ...
)
## 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

mod

A fitted SEM model (cSEM).

indep

A string indicating the name of the independent variable in the model.

med

A string indicating the name of the mediator variable in the model.

dep

A string indicating the name of the dependent variable in the model.

approach

either 'bk' or 'zlc' or both c("bk", "zlc") (default)

p.threshold

A double giving the p-value for determining whether a path is significant or not

effect.size

calculate different effect-sizes; one or more of "RIT", "RID"

nbootstrap

number of bootstrap samples, default=1000

ci.two.tailed

A double giving the confidence level for two-tailed confidence intervals (default 0.95)

...

additional arguments (currently unused)

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,
  ...
)
## 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

mod

A fitted SEM model (lavaan).

indep

A string indicating the name of the independent variable in the model.

med

A string indicating the name of the mediator variable in the model.

dep

A string indicating the name of the dependent variable in the model.

approach

either 'bk' or 'zlc' or both c("bk", "zlc") (default)

p.threshold

A double giving the p-value for determining whether a path is significant or not

effect.size

calculate different effect-sizes; one or more of "RIT", "RID"

standardized

A boolean indicating whether the coefficients should be standardized. The default value is FALSE.

mcreps

An integer determining the number of monte-carlo samples.

ci.two.tailed

A double giving the confidence level for two-tailed confidence intervals (default 0.95)

...

additional arguments (currently unused)

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)

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,
  ...
)
## 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

mod

A fitted SEM model (modsem).

indep

A string indicating the name of the independent variable in the model.

med

A string indicating the name of the mediator variable in the model.

dep

A string indicating the name of the dependent variable in the model.

approach

either 'bk' or 'zlc' or both c("bk", "zlc") (default)

p.threshold

A double giving the p-value for determining whether a path is significant or not

effect.size

calculate different effect-sizes; one or more of "RIT", "RID"

moderator

A string indicating the name of the moderator variable in the model.

standardized

A boolean indicating whether the coefficients should be standardized. The default value is FALSE.

mcreps

An integer determining the number of monte-carlo samples.

ci.two.tailed

A double giving the confidence level for two-tailed confidence intervals (default 0.95)

...

additional arguments (currently unused)

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")
}


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

Arguments

object

the rmedsem object

...

additional arguments passed to print.rmedsem()

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)

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)

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, ...)
Upsilon(res, ...)

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

Arguments

res

fitted rmedsem object

...

additional arguments (currently unused)

adjusted

logical; if TRUE (default), return the bias-adjusted estimator; if FALSE, return the unadjusted estimator

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)

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)

Fitness Center Survey Data from Trondheim

Description

Data from a survey in a fitness center in Trondheim.

Usage

workout
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

Package 'rmedsem'

Help Index

Convert an rmedsem Object to a Data Frame

Description

Usage

Arguments

Value

Examples

High School and Beyond Demo Dataset

Description

Usage

Format

hsbdemo

Mate-Choice Survey Data from Trondheim

Description

Usage

Format

mchoice

Plot Coefficients for an rmedsem Object

Description

Usage

Arguments

Value

Examples

Plot Effect Sizes for an rmedsem Object

Description

Usage

Arguments

Value

Examples

Plot an rmedsem Object

Description

Usage

Arguments

Value

Examples

Print an rmedsem Object

Description

Usage

Arguments

Value

Examples

Ratio of Indirect to Direct Effect (RID)

Description

Usage

Arguments

Value

Examples

Ratio of Indirect to Total Effect (RIT)

Description

Usage

Arguments

Value

Examples

Mediation Analysis for Structural Equation Models

Description

Usage

Arguments

Value

Examples

Mediation Analysis for Blavaan Models

Description

Usage

Arguments

Value

Examples

Mediation Analysis for cSEM Models

Description

Usage

Arguments

Value

Mediation Analysis for Lavaan Models

Description

Usage

Arguments

Value

Examples

Mediation Analysis for Modsem Models

Description

Usage

`hsbdemo`

`mchoice`

`workout`