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

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

if (FALSE) { # \dontrun{
# 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)
} # }