Generate a population correlation matrix using the model described in Cudeck
and Browne (1992). This function uses the implementation of the Cudeck and
Browne method from Ken Kelley's MBESS package.

Computes fungible coefficients and Monte Carlo data. Underlying theory for these functions is described in the following publications:
Waller, N. (2008). Fungible Weights in Multiple Regression. Psychometrika, 73(4), 691-703, <DOI:10.1007/s11336-008-9066-z>.
Waller, N. & Jones, J. (2009). Locating the Extrema of Fungible Regression Weights.
Psychometrika, 74(4), 589-602, <DOI:10.1007/s11336-008-9087-7>.
Waller, N. G. (2016). Fungible Correlation Matrices:
A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for
Monte Carlo Research. Multivariate Behavioral Research, 51(4), 554-568.
Jones, J. A. & Waller, N. G. (2015). The normal-theory and asymptotic distribution-free (ADF)
covariance matrix of standardized regression coefficients: theoretical extensions
and finite sample behavior. Psychometrika, 80, 365-378, <DOI:10.1007/s11336-013-9380-y>.
Waller, N. G. (2018). Direct Schmid-Leiman transformations and rank-deficient loadings matrices. Psychometrika, 83, 858-870. <DOI:10.1007/s11336-017-9599-0>.

Niels G Waller

fungible

Psychometric Functions from the Waller Lab

Niels Waller

Justin Kracht

Jeff Jones

Casey Giordano

Hoang V. Nguyen 

cb function

<dl><dt>mod</dt>
<dd>A `fungible::simFA()` model object.</dd>
<dt>target_rmsea</dt>
<dd>(scalar) Target RMSEA value.</dd></dl>

Arguments

Cudeck &amp; Browne (1992) model error method — cb

<dl>

<dt>mod</dt>
<dd>A `fungible::simFA()` model object.</dd>


<dt>target_rmsea</dt>
<dd>(scalar) Target RMSEA value.</dd>

</dl>

cb: Cudeck & Browne (1992) model error method

Description

Usage

Arguments

References