rmsea: Calculate RMSEA between two correlation matrices

In fungible: Psychometric Functions from the Waller Lab

Calculate RMSEA between two correlation matrices

Description

Given two correlation matrices of the same dimension, calculate the RMSEA value using the degrees of freedom for the exploratory factor analysis model (see details).

Usage

rmsea(Sigma, Omega, k)

Arguments

Sigma	(matrix) Population correlation or covariance matrix (with model error).
Omega	(matrix) Model-implied population correlation or covariance matrix.
k	(scalar) Number of major common factors.

Details

Note that this function uses the degrees of freedom for an exploratory factor analysis model:

df = p(p-1)/2-(pk)+k(k-1)/2,

where p is the number of items and k is the number of major factors.

Examples

mod <- fungible::simFA(Model = list(NFac = 3),
                       Seed = 42)
set.seed(42)
Omega <- mod$Rpop
Sigma <- noisemaker(
  mod = mod,
  method = "CB",
  target_rmsea = 0.05
)$Sigma
rmsea(Sigma, Omega, k = 3)

fungible documentation built on May 29, 2024, 8:28 a.m.