model_parameters.lavaan: Parameters from CFA/SEM models

Description

Format CFA/SEM objects from the lavaan package (Rosseel, 2012; Merkle and Rosseel 2018).

Usage

# S3 method for lavaan
model_parameters(
  model,
  ci = 0.95,
  standardize = FALSE,
  component = c("regression", "correlation", "loading", "defined"),
  parameters = NULL,
  verbose = TRUE,
  ...
)

Arguments

model

CFA or SEM created by the lavaan::cfa or lavaan::sem functions.

Confidence Interval (CI) level. Default to 0.95 (95%).

standardize

Return standardized parameters (standardized coefficients). Can be TRUE (or "all" or "std.all") for standardized estimates based on both the variances of observed and latent variables; "latent" (or "std.lv") for standardized estimates based on the variances of the latent variables only; or "no_exogenous" (or "std.nox") for standardized estimates based on both the variances of observed and latent variables, but not the variances of exogenous covariates. See lavaan::standardizedsolution for details.

component

What type of links to return. Can be "all" or some of c("regression", "correlation", "loading", "variance", "mean").

parameters

Character vector of length 1 with a regular expression pattern that describes the parameters that should be returned from the data frame, or a named list of regular expressions. All non-matching parameters will be removed from the output. If parameters is a character vector, every parameter in the "Parameters" column that matches the regular expression in parameters will be selected from the returned data frame. Furthermore, if parameters has more than one element, these will be merged into a regular expression pattern like this: "(one|two|three)". If parameters is a named list of regular expression patterns, the names of the list-element should equal the column name where selection should be applied. This is useful for model objects where model_parameters() returns multiple columns with parameter components, like in model_parameters.lavaan.

verbose

Toggle warnings and messages.

...

Arguments passed to or from other methods.

Value

A data frame of indices related to the model's parameters.

References

Rosseel Y (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36.
Merkle EC , Rosseel Y (2018). blavaan: Bayesian Structural Equation Models via Parameter Expansion. Journal of Statistical Software, 85(4), 1-30. http://www.jstatsoft.org/v85/i04/

Examples

Run this code

# NOT RUN {
library(parameters)

# lavaan -------------------------------------
if (require("lavaan", quietly = TRUE)) {

  # Confirmatory Factor Analysis (CFA) ---------

  structure <- " visual  =~ x1 + x2 + x3
                 textual =~ x4 + x5 + x6
                 speed   =~ x7 + x8 + x9 "
  model <- lavaan::cfa(structure, data = HolzingerSwineford1939)
  model_parameters(model)
  model_parameters(model, standardize = TRUE)

  # filter parameters
  model_parameters(
    model,
    parameters = list(
      To = "^(?!visual)",
      From = "^(?!(x7|x8))"
    )
  )

  # Structural Equation Model (SEM) ------------

  structure <- "
    # latent variable definitions
      ind60 =~ x1 + x2 + x3
      dem60 =~ y1 + a*y2 + b*y3 + c*y4
      dem65 =~ y5 + a*y6 + b*y7 + c*y8
    # regressions
      dem60 ~ ind60
      dem65 ~ ind60 + dem60
    # residual correlations
      y1 ~~ y5
      y2 ~~ y4 + y6
      y3 ~~ y7
      y4 ~~ y8
      y6 ~~ y8
  "
  model <- lavaan::sem(structure, data = PoliticalDemocracy)
  model_parameters(model)
  model_parameters(model, standardize = TRUE)
}
# }