CFA: Confirmatory Factor Analysis (CFA).

In bruceR: Broadly Useful Convenient and Efficient R Functions

Confirmatory Factor Analysis (CFA).

Description

An extension of lavaan::cfa().

Usage

CFA(
  data,
  model = "A =~ a[1:5]; B =~ b[c(1,3,5)]; C =~ c1 + c2 + c3",
  estimator = "ML",
  highorder = "",
  orthogonal = FALSE,
  missing = "listwise",
  digits = 3,
  file = NULL
)

Arguments

data	Data frame.
model	Model formula. See examples.
estimator	The estimator to be used (for details, see lavaan options). Defaults to "ML". Can be one of the following: "ML" Maximum Likelihood (can be extended to "MLM", "MLMV", "MLMVS", "MLF", or "MLR" for robust standard errors and robust test statistics) "GLS" Generalized Least Squares "WLS" Weighted Least Squares "ULS" Unweighted Least Squares "DWLS" Diagonally Weighted Least Squares "DLS" Distributionally-weighted Least Squares
highorder	High-order factor. Defaults to "".
orthogonal	Defaults to FALSE. If TRUE, all covariances among latent variables are set to zero.
missing	Defaults to "listwise". Alternative is "fiml" ("Full Information Maximum Likelihood").
digits	Number of decimal places of output. Defaults to 3.
file	File name of MS Word (.doc).

Value

A list of results returned by lavaan::cfa().

See Also

Alpha, EFA, lavaan_summary

Examples

data.cfa=lavaan::HolzingerSwineford1939
CFA(data.cfa, "Visual =~ x[1:3]; Textual =~ x[c(4,5,6)]; Speed =~ x7 + x8 + x9")
CFA(data.cfa, model="
    Visual =~ x[1:3]
    Textual =~ x[c(4,5,6)]
    Speed =~ x7 + x8 + x9
    ", highorder="Ability")

data.bfi = na.omit(psych::bfi)
CFA(data.bfi, "E =~ E[1:5]; A =~ A[1:5]; C =~ C[1:5]; N =~ N[1:5]; O =~ O[1:5]")

bruceR documentation built on June 22, 2024, 12:26 p.m.