Estimation latent interactions through Mplus

Estimation latent interactions through Mplus

Usage

modsem_mplus(
  model.syntax,
  data,
  estimator = "ml",
  cluster = NULL,
  type = ifelse(is.null(cluster), yes = "random", no = "complex"),
  algorithm = "integration",
  processors = 2,
  integration = 15,
  rcs = FALSE,
  rcs.choose = NULL,
  rcs.scale.corrected = TRUE,
  output.std = TRUE,
  ...
)

Arguments

model.syntax: lavaan/modsem syntax
data: dataset
estimator: estimator argument passed to Mplus.
cluster: cluster argument passed to Mplus.
type: type argument passed to Mplus.
algorithm: algorithm argument passed to Mplus.
processors: processors argument passed to Mplus.
integration: integration argument passed to Mplus.
rcs: Should latent variable indicators be replaced with reliability-corrected single item indicators instead? See relcorr_single_item.
rcs.choose: Which latent variables should get their indicators replaced with reliability-corrected single items? It is passed to relcorr_single_item as the choose argument.
rcs.scale.corrected: Should reliability-corrected items be scale-corrected? If TRUE reliability-corrected single items are corrected for differences in factor loadings between the items. Default is TRUE.
output.std: Should STANDARDIZED be added to OUTPUT?
...: arguments passed to other functions

Value

modsem_mplus object

Examples

# Theory Of Planned Behavior
m1 <- '
# Outer Model
  X =~ x1 + x2
  Z =~ z1 + z2
  Y =~ y1 + y2

# Inner model
  Y ~ X + Z + X:Z
'

# \dontrun{
# Check if Mplus is installed
run <- tryCatch({MplusAutomation::detectMplus(); TRUE},
                error = \(e) FALSE)

if (run) {
  est_mplus <- modsem_mplus(m1, data = oneInt)
  summary(est_mplus)
}
# }