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fungible (version 2.4.4)

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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Install

install.packages('fungible')

Monthly Downloads

2,914

Version

2.4.4

License

GPL (>= 2)

Maintainer

Niels G Waller

Last Published

March 9th, 2024

Functions in fungible (2.4.4)

GenerateBoxData

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

Utility function for checking FMP monotonicity
CompleteRmap

Complete a Partially Specified Correlation Matrix by the Method of Alternating Projections
CompleteRdev

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

Six data sets that yield a Heywood case
HS9Var

9 Variables from the Holzinger and Swineford (1939) Dataset
FMP

Estimate the coefficients of a filtered monotonic polynomial IRT model
FUP

Estimate the coefficients of a filtered unconstrained polynomial IRT model
Box26

R matrix for Thurstone's 26 hypothetical box attributes.
CompleteRcvx

Complete a Partially Specified Correlation Matrix by Convex Optimization
RGen

Generate random R matrices with various user-defined properties via differential evolution (DE).
Rbounds

Generate random R matrices with user-defined bounds on the correlation coefficients via differential evolution (DE).
Omega

Compute Omega hierarchical
Jackson67

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

Conduct a Schmid-Leiman Iterated (SLi) Target Rotation
SchmidLeiman

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

Ledermann's inequality for factor solution identification
Ravgr

Generate a random R matrix with an average rij
RnpdMAP

Generate Random NPD R matrices from a user-supplied population R
Malmi79

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

Asymptotic Distribution-Free Covariance Matrix of Covariances
alphaR

Generate random R matrices with a known coefficient alpha
VolElliptope

Compute the volume of the elliptope of possible correlation matrices of a given dimension.
ThurstoneBox26

Factor Pattern Matrix for Thurstone's 26 box attributes.
ThurstoneBox20

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

Estimate the parameters of the Taylor-Russell function.
bigen

Generate Correlated Binary Data
adfCor

Asymptotic Distribution-Free Covariance Matrix of Correlations
Thurstone41

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

Smooth a Non PD Correlation Matrix
eigGen

Generate eigenvalues for R matrices with underlying component structure
d2r

Convert Degrees to Radians
TaylorRussell

A generalized (multiple predictor) Taylor-Russell function.
cfi

Calculate CFI for two correlation matrices
cb

Cudeck & Browne (1992) model error method
eap

Compute eap trait estimates for FMP and FUP models
cosMat

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

Generate the marginal density of a correlation from a uniformly sampled R matrix.
corSample

Sample Correlation Matrices from a Population Correlation Matrix
enhancement

Find OLS Regression Coefficients that Exhibit Enhancement
faAlign

Align the columns of two factor loading matrices
faIB

Inter-Battery Factor Analysis by the Method of Maximum Likelihood
faScores

Factor Scores
faMain

Automatic Factor Rotation from Random Configurations with Bootstrap Standard Errors
faBounds

Bounds on the Correlation Between an External Variable and a Common Factor
faMB

Multiple Battery Factor Analysis by Maximum Likelihood Methods
faEKC

Calculate Reference Eigenvalues for the Empirical Kaiser Criterion
erf

Utility fnc to compute the components for an empirical response function
faLocalMin

Investigate local minima in faMain objects
faMAP

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

Sort a factor loadings matrix
faStandardize

Standardize the Unrotated Factor Loadings
fapa

Iterated Principal Axis Factor Analysis (fapa)
fareg

Regularized Factor Analysis
faX

Factor Extraction (faX) Routines
fsIndeterminacy

Understanding Factor Score Indeterminacy with Finite Dimensional Vector Spaces
fungibleExtrema

Locate Extrema of Fungible Regression Weights
fals

Unweighted least squares factor analysis
fungibleL

Generate Fungible Logistic Regression Weights
fungible

Generate Fungible Regression Weights
monte

Simulate Clustered Data with User-Defined Properties
get_wb_mod

Find an `lm` model to use with the Wu & Browne (2015) model error method
genCorr

Generate Correlation Matrices with User-Defined Eigenvalues
genFMPData

Generate item response data for a filtered monotonic polynomial IRT model
genPhi

Create a random Phi matrix with maximum factor correlation
irf

Plot item response functions for polynomial IRT models.
kurt

Calculate Univariate Kurtosis for a Vector or Matrix
itemDescriptives

Compute basic descriptives for binary-item analysis
fungibleR

Generate Fungible Correlation Matrices
gen4PMData

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

Print Method for an Object of Class faMB
orderFactors

Order factor-loadings matrix by the sum of squared factor loadings
plot.monte

Plot Method for Class Monte
print.faMain

Print Method for an Object of Class faMain
noisemaker

Simulate a population correlation matrix with model error
monte1

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

Objective function for optimizing RMSEA and CFI
promaxQ

Conduct an Oblique Promax Rotation
normalCor

Compute Normal-Theory Covariances for Correlations
normF

Compute the Frobenius norm of a matrix
rarc

Rotate Points on the Surface on an N-Dimensional Ellipsoid
rmsd

Root Mean Squared Deviation of (A - B)
rMAP

Generate Correlation Matrices with Specified Eigenvalues
rcor

Generate Random PSD Correlation Matrices
restScore

Plot an ERF using rest scores
rPCA

Generate a Correlation Matrix from a Truncated PCA Loadings Matrix.
rellipsoid

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

Generate a Cone of Regression Coefficient Vectors
rGivens

Generate Correlation Matrices with Specified Eigenvalues
r2d

Convert Radians to Degrees
smoothKB

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

Calculate RMSEA between two correlation matrices
seBeta

Standard Errors and CIs for Standardized Regression Coefficients
smoothBY

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

Calculate Univariate Skewness for a Vector or Matrix
seBetaCor

Standard Errors and CIs for Standardized Regression Coefficients from Correlations
seBetaFixed

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

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

Generate Factor Analysis Models and Data Sets for Simulation Studies
semify

Generate an sem model from a simFA model object
summary.monte1

Summary Method for an Object of Class Monte1
summary.faMain

Summary Method for an Object of Class faMain
wb

Wu & Browne model error method
smoothLG

Smooth NPD to Nearest PSD or PD Matrix
svdNorm

Compute theta surrogates via normalized SVD scores
vnorm

Norm a Vector to Unit Length
summary.faMB

Summary Method for an Object of Class faMB
summary.monte

Summary Method for an Object of Class Monte
tkl

Optimize TKL parameters to find a solution with target RMSEA and CFI values
vcos

Compute the Cosine Between Two Vectors
tetcor

Compute ML Tetrachoric Correlations
tetcorQuasi

Correlation between a Naturally and an Artificially Dichotomized Variable
AmzBoxes

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

Bifactor Analysis via Direct Schmid-Leiman (DSL) Transformations
BadRKtB

Improper R matrix reported by Knol and ten Berge
ACL

Adjective Checklist Data.
BadRJN

Improper R matrix reported by Joseph and Newman
BadRRM

Improper R matrix reported by Rousseeuw and Molenberghs
Box20

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

Improper correlation matrix reported by Bentler and Yuan
Boruch70

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

Improper R matrix reported by Lurie and Goldberg