Calculate a mediation analysis for an SEM based on a modsem model.

Calculate a mediation analysis for an SEM based on a modsem model.

Usage

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

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 F.

mcreps

An integer determining the number of monte-carlo samples.

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"

Value

A rmedsem structure containing the results from the analysis

Examples

if (FALSE) { # \dontrun{

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(m, data = mchoice2, 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")

} # }