fungible - Psychometric Functions from the Waller Lab
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>.
