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>.

Package details

AuthorNiels Waller [aut, cre], Justin Kracht [ctb], Jeff Jones [ctb], Casey Giordano [ctb], Hoang V. Nguyen [ctb]
MaintainerNiels Waller <nwaller@umn.edu>
LicenseGPL (>= 2)
Version2.4.4
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("fungible")

Try the fungible package in your browser

Any scripts or data that you put into this service are public.

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