parameter_estimates: Extract parameterEstimates from an estimated model

In modsem: Latent Interaction (and Moderation) Analysis in Structural Equation Models (SEM)

Extract parameterEstimates from an estimated model

Description

Extract parameterEstimates from an estimated model

Usage

parameter_estimates(object, ...)

## S3 method for class 'lavaan'
parameter_estimates(
  object,
  colon.pi = NULL,
  high.order.as.measr = NULL,
  rm.tmp.ov = NULL,
  label.renamed.prod = NULL,
  is.public = NULL,
  ...
)

## S3 method for class 'modsem_da'
parameter_estimates(
  object,
  high.order.as.measr = TRUE,
  is.public = TRUE,
  rm.tmp.ov = is.public,
  label.renamed.prod = NULL,
  ...
)

## S3 method for class 'modsem_mplus'
parameter_estimates(
  object,
  colon.pi = NULL,
  high.order.as.measr = NULL,
  rm.tmp.ov = NULL,
  label.renamed.prod = NULL,
  is.public = NULL,
  ...
)

## S3 method for class 'modsem_pi'
parameter_estimates(
  object,
  colon.pi = FALSE,
  label.renamed.prod = FALSE,
  high.order.as.measr = NULL,
  rm.tmp.ov = NULL,
  is.public = NULL,
  ...
)

Arguments

object	An object of class modsem_pi, modsem_da, or modsem_mplus
...	Additional arguments passed to other functions
colon.pi	Should colons (:) be added to the interaction terms (E.g., 'XZ' -> 'X:Z')?
high.order.as.measr	Should higher order measurement model be denoted with the =~ operator? If FALSE the ~ operator is used.
rm.tmp.ov	Should temporary (hidden) variables be removed?
label.renamed.prod	Should renamed product terms keep their old (implicit) labels?
is.public	Should public version of parameter table be returned? If FALSE, the internal version of the parameter table is returned.

Methods (by class)

• parameter_estimates(lavaan): Get parameter estimates of a lavaan object

• parameter_estimates(modsem_da): Get parameter estimates of a modsem_da object

• parameter_estimates(modsem_mplus): Get parameter estimates of a modsem_mplus object

• parameter_estimates(modsem_pi): Get parameter estimates of a modsem_pi object

Examples

m1 <- '
  # Outer Model
  X =~ x1 + x2 + x3
  Z =~ z1 + z2 + z3
  Y =~ y1 + y2 + y3

  # Inner Model
  Y ~ X + Z + X:Z
'
# Double centering approach
est_dca <- modsem(m1, oneInt)

pars <- parameter_estimates(est_dca) # no correction

# Pretty summary
summarize_partable(pars)

# Only print the data.frame
pars

modsem documentation built on Jan. 23, 2026, 5:07 p.m.