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fungible (version 1.97)

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

2,823

Version

1.97

License

GPL (>= 2)

Maintainer

Niels G Waller

Last Published

April 1st, 2021

Functions in fungible (1.97)

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

Bifactor Analysis via Direct Schmid-Leiman (DSL) Transformations

Improper R matrix reported by Knol and ten Berge

Improper R matrix reported by Joseph and Newman

Improper R matrix reported by Rousseeuw and Molenberghs

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

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

Adjective Checklist Data.

Improper R matrix reported by Lurie and Goldberg

Improper correlation matrix reported by Bentler and Yuan

GenerateBoxData

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

Six data sets that yield a Heywood case

9 Variables from the Holzinger and Swineford (1939) Dataset

Generate Correlated Binary Data

Asymptotic Distribution-Free Covariance Matrix of Covariances

Compute Omega hierarchical

R matrix for Thurstone's 26 hypothetical box attributes.

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

Estimate the coefficients of a filtered monotonic polynomial IRT model

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

Conduct a Schmid-Leiman Iterated (SLi) Target Rotation

Estimate the coefficients of a filtered unconstrained polynomial IRT model

FMPMonotonicityCheck

Utility function for checking FMP monotonicity

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

Ledermann's inequality for factor solution identification

Align the columns of two factor loading matrices

Calculate Reference Eigenvalues for the Empirical Kaiser Criterion

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

Sample Correlation Matrices from a Population Correlation Matrix

Find OLS Regression Coefficients that Exhibit Enhancement

Utility fnc to compute the components for an empirical response function

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

Investigate local minima in faMain objects

Inter-Battery Factor Analysis by the Method of Maximum Likelihood

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

Automatic Factor Rotation from Random Configurations with Bootstrap Standard Errors

Smooth a Non PD Correlation Matrix

Asymptotic Distribution-Free Covariance Matrix of Correlations

Generate eigenvalues for R matrices with underlying component structure

Factor Pattern Matrix for Thurstone's 26 box attributes.

Plot Method for Class Monte

Generate Correlation Matrices with User-Defined Eigenvalues

Generate Fungible Logistic Regression Weights

Compute eap trait estimates for FMP and FUP models

Print Method for an Object of Class faMB

Generate Fungible Correlation Matrices

Multiple Battery Factor Analysis by Maximum Likelihood Methods

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

Compute the Frobenius norm of a matrix

Root Mean Squared Deviation of (A - B)

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

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

Generate Correlation Matrices with Specified Eigenvalues

Rotate Points on the Surface on an N-Dimensional Ellipsoid

Convert Degrees to Radians

Standard Errors and CIs for Standardized Regression Coefficients from Correlations

Factor Extraction (faX) Routines

Unweighted least squares factor analysis

Standardize the Unrotated Factor Loadings

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

Sort a factor loadings matrix

Summary Method for an Object of Class faMB

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

Summary Method for an Object of Class faMain

Iterated Principal Axis Factor Analysis (fapa)

Regularized Factor Analysis

Calculate Univariate Kurtosis for a Vector or Matrix

Standard Errors and CIs for Standardized Regression Coefficients

Compute theta surrogates via normalized SVD scores

Compute Normal-Theory Covariances for Correlations

Generate Fungible Regression Weights

Convert Radians to Degrees

Generate Correlation Matrices with Specified Eigenvalues

Simulate Clustered Data with User-Defined Properties

Plot item response functions for polynomial IRT models.

itemDescriptives

Compute basic descriptives for binary-item analysis

fungibleExtrema

Locate Extrema of Fungible Regression Weights

Create a random Phi matrix with maximum factor correlation

Generate item response data for a filtered monotonic polynomial IRT model

Generate a Cone of Regression Coefficient Vectors

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

Generate Random PSD Correlation Matrices

Print Method for an Object of Class faMain

Compute ML Tetrachoric Correlations

Calculate Univariate Skewness for a Vector or Matrix

Generate Factor Analysis Models and Data Sets for Simulation Studies

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

Summary Method for an Object of Class Monte1

Summary Method for an Object of Class Monte

Norm a Vector to Unit Length

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

Conduct an Oblique Promax Rotation

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

Compute the Cosine Between Two Vectors

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

Plot an ERF using rest scores

Smooth NPD to Nearest PSD or PD Matrix

Correlation between a Naturally and an Artificially Dichotomized Variable