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fungible (version 2.2)

Psychometric Functions from the Waller Lab

Description

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, . Waller, N. & Jones, J. (2009). Locating the Extrema of Fungible Regression Weights. Psychometrika, 74(4), 589-602, . 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, . Waller, N. G. (2018). Direct Schmid-Leiman transformations and rank-deficient loadings matrices. Psychometrika, 83, 858-870. .

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Version

Install

install.packages('fungible')

Monthly Downloads

3,895

Version

2.2

License

GPL (>= 2)

Maintainer

Niels G Waller

Last Published

April 26th, 2022

Functions in fungible (2.2)

Adjective Checklist Data.

Improper R matrix reported by Rousseeuw and Molenberghs

Improper R matrix reported by Knol and ten Berge

Improper R matrix reported by Joseph and Newman

Length, width, and height measurements for Thurstone's 20 boxes

Length, width, and height measurements for 98 Amazon shipping boxes

Improper correlation matrix reported by Bentler and Yuan

Improper R matrix reported by Lurie and Goldberg

Bifactor Analysis via Direct Schmid-Leiman (DSL) Transformations

Multi-Trait Multi-Method correlation matrix reported by Boruch, Larkin, Wolins, and MacKinney (1970)

R matrix for Thurstone's 26 hypothetical box attributes.

Multi-Trait Multi-Method correlation matrix reported by Jackson and Singer (1967)

Six data sets that yield a Heywood case

FMPMonotonicityCheck

Utility function for checking FMP monotonicity

Estimate the coefficients of a filtered unconstrained polynomial IRT model

9 Variables from the Holzinger and Swineford (1939) Dataset

GenerateBoxData

Generate Thurstone's Box Data From length, width, and height box measurements

Compute Omega hierarchical

Generate Random NPD R matrices from a user-supplied population R

Estimate the coefficients of a filtered monotonic polynomial IRT model

Complete a Partially Specified Correlation Matrix by the Method of Differential Evolution

Schmid-Leiman Orthogonalization to a (Rank-Deficient) Bifactor Structure

Multi-Trait Multi-Method correlation matrix reported by Thurstone and Thurstone (1941).

Conduct a Schmid-Leiman Iterated (SLi) Target Rotation

Factor Pattern and Factor Correlations for Thurstone's 20 hypothetical box attributes.

Ledermann's inequality for factor solution identification

Utility fnc to compute the components for an empirical response function

Find OLS Regression Coefficients that Exhibit Enhancement

Complete a Partially Specified Correlation Matrix by Convex Optimization

Multi-Trait Multi-Method correlation matrix reported by Malmi, Underwood, and Carroll (1979).

Factor Pattern Matrix for Thurstone's 26 box attributes.

Compute eap trait estimates for FMP and FUP models

Generate eigenvalues for R matrices with underlying component structure

Sample Correlation Matrices from a Population Correlation Matrix

Smooth a Non PD Correlation Matrix

Compute the cosine(s) between either 2 matrices or 2 vectors.

Asymptotic Distribution-Free Covariance Matrix of Correlations

Convert Degrees to Radians

Generate Correlated Binary Data

Asymptotic Distribution-Free Covariance Matrix of Covariances

Investigate local minima in faMain objects

Inter-Battery Factor Analysis by the Method of Maximum Likelihood

Standardize the Unrotated Factor Loadings

Sort a factor loadings matrix

Calculate Reference Eigenvalues for the Empirical Kaiser Criterion

Align the columns of two factor loading matrices

Automatic Factor Rotation from Random Configurations with Bootstrap Standard Errors

Generate item response data for 1, 2, 3, or 4-parameter IRT models

Generate Fungible Correlation Matrices

fungibleExtrema

Locate Extrema of Fungible Regression Weights

Generate Fungible Logistic Regression Weights

Compute Normal-Theory Covariances for Correlations

Compute the Frobenius norm of a matrix

Iterated Principal Axis Factor Analysis (fapa)

itemDescriptives

Compute basic descriptives for binary-item analysis

Velicer's minimum partial correlation method for determining the number of major components for a principal components analysis or a factor analysis

Regularized Factor Analysis

Multiple Battery Factor Analysis by Maximum Likelihood Methods

Factor Extraction (faX) Routines

Generate a Correlation Matrix from a Truncated PCA Loadings Matrix.

Rotate Points on the Surface on an N-Dimensional Ellipsoid

Create a random Phi matrix with maximum factor correlation

Conduct an Oblique Promax Rotation

Convert Radians to Degrees

Plot item response functions for polynomial IRT models.

Order factor-loadings matrix by the sum of squared factor loadings

Calculate Univariate Kurtosis for a Vector or Matrix

Plot Method for Class Monte

Generate Correlation Matrices with User-Defined Eigenvalues

Unweighted least squares factor analysis

Smooth a NPD R matrix to PD using the Alternating Projection Algorithm

Generate Uniformly Spaced OLS Regression Coefficients that Yield a User-Supplied R-Squared Value

Plot an ERF using rest scores

Smooth an NPD R matrix to PD using the Bentler Yuan 2011 method

Standard Errors and CIs for Standardized Regression Coefficients

Root Mean Squared Deviation of (A - B)

Generate item response data for a filtered monotonic polynomial IRT model

Norm a Vector to Unit Length

Generate Correlation Matrices with Specified Eigenvalues

Generate Correlation Matrices with Specified Eigenvalues

Covariance Matrix and Standard Errors for Standardized Regression Coefficients for Fixed Predictors

Standard Errors and CIs for Standardized Regression Coefficients from Correlations

Summary Method for an Object of Class Monte

Summary Method for an Object of Class faMain

Summary Method for an Object of Class faMB

Generate Factor Analysis Models and Data Sets for Simulation Studies

Calculate Univariate Skewness for a Vector or Matrix

Compute ML Tetrachoric Correlations

Compute theta surrogates via normalized SVD scores

fsIndeterminacy

Understanding Factor Score Indeterminacy with Finite Dimensional Vector Spaces

Generate Fungible Regression Weights

Print Method for an Object of Class faMB

Simulate Multivariate Non-normal Data by Vale & Maurelli (1983) Method

Simulate Clustered Data with User-Defined Properties

Summary Method for an Object of Class Monte1

Compute the Cosine Between Two Vectors

Correlation between a Naturally and an Artificially Dichotomized Variable

Print Method for an Object of Class faMain

Generate Random PSD Correlation Matrices

Smooth NPD to Nearest PSD or PD Matrix

Generate a Cone of Regression Coefficient Vectors

Smooth a Non PD Correlation Matrix using the Knol-Berger algorithm