rmsea {fungible} | R Documentation |
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)
[Package fungible version 2.4.4 Index]