parameters (version 0.10.1)

model_parameters.lavaan: Parameters from CFA/SEM models

Description

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

Usage

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

Arguments

model

CFA or SEM created by the lavaan::cfa or lavaan::sem functions (or from blavaan).

ci

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.

type

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

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

# NOT RUN {
library(parameters)

# lavaan -------------------------------------
if (require("lavaan")) {

  # 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)

  # 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)
}
# }