Package: nFactors 2.4.1.1

nFactors: Parallel Analysis and Other Non Graphical Solutions to the Cattell Scree Test

Indices, heuristics and strategies to help determine the number of factors/components to retain: 1. Acceleration factor (af with or without Parallel Analysis); 2. Optimal Coordinates (noc with or without Parallel Analysis); 3. Parallel analysis (components, factors and bootstrap); 4. lambda > mean(lambda) (Kaiser, CFA and related); 5. Cattell-Nelson-Gorsuch (CNG); 6. Zoski and Jurs multiple regression (b, t and p); 7. Zoski and Jurs standard error of the regression coeffcient (sescree); 8. Nelson R2; 9. Bartlett khi-2; 10. Anderson khi-2; 11. Lawley khi-2 and 12. Bentler-Yuan khi-2.

Authors:Gilles Raiche and David Magis

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nFactors.pdf |nFactors.html✨
nFactors/json (API)
NEWS

# Install 'nFactors' in R:
install.packages('nFactors', repos = c('https://raicheg.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • dFactors - Eigenvalues from classical studies

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5.57 score 4 packages 496 scripts 6.3k downloads 39 mentions 29 exports 6 dependencies

Last updated 2 years agofrom:0d077e574b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-winOKNov 13 2024
R-4.5-linuxOKNov 13 2024
R-4.4-winOKNov 13 2024
R-4.4-macOKNov 13 2024
R-4.3-winOKNov 13 2024
R-4.3-macOKNov 13 2024

Exports:bentlerParameterscomponentAxiscorFAdiagReplaceeigenBootParalleleigenComputeseigenFromgenerateStructureis.nFactorsis.nScreeis.structureSimiterativePrincipalAxismakeCormoreStatsnBartlettnBentlernCngnMregnScreenSeScreeparallelplotnScreeplotParallelplotuScreeprincipalAxisprincipalComponentsrRecoverystructureSimstudySim

Dependencies:GPArotationlatticeMASSmnormtnlmepsych

Readme and manuals

Help Manual

Help pageTopics
Bentler and Yuan's Computation of the LRT Index and the Linear Trend CoefficientsbentlerParameters
Principal Component Analysis With Only n First Components RetainedcomponentAxis
Insert Communalities in the Diagonal of a Correlation or a Covariance MatrixcorFA
Eigenvalues from classical studiesdFactors
Replacing Upper or Lower Diagonal of a Correlation or Covariance MatrixdiagReplace
Bootstrapping of the Eigenvalues From a Data FrameeigenBootParallel
Computes Eigenvalues According to the Data TypeeigenComputes
Identify the Data Type to Obtain the EigenvalueseigenFrom
Generate a Factor Structure MatrixgenerateStructure
Utility Functions for nFactors Class Objectsis.nFactors print.nFactors summary.nFactors
Iterative Principal Axis AnalysisiterativePrincipalAxis
Create a Full Correlation/Covariance Matrix from a Matrix With Lower Part Filled and Upper Part With ZerosmakeCor
Statistical Summary of a Data FramemoreStats
Bartlett, Anderson and Lawley Procedures to Determine the Number of Components/FactorsnBartlett
Bentler and Yuan's Procedure to Determine the Number of Components/FactorsnBentler
Cattell-Nelson-Gorsuch CNG IndicesnCng
nFactors: Number of factor or components to retain in a factor analysisnFactors-package nFactors
Multiple Regression Procedure to Determine the Number of Components/FactorsnMreg
Non Graphical Cattel's Scree TestnScree
Standard Error Scree and Coefficient of Determination Procedures to Determine the Number of Components/FactorsnSeScree
Parallel Analysis of a Correlation or Covariance Matrixparallel
Scree Plot According to a nScree Object ClassplotnScree
Plot a Parallel Analysis Class ObjectplotParallel
Plot of the Usual Cattell's Scree TestplotuScree
Principal Axis AnalysisprincipalAxis
Principal Component AnalysisprincipalComponents
Test of Recovery of a Correlation or a Covariance matrix from a Factor Analysis SolutionrRecovery
Population or Simulated Sample Correlation Matrix from a Given Factor Structure MatrixstructureSim
Simulation Study from Given Factor Structure Matrices and ConditionsstudySim
Utility Functions for nScree Class Objectsis.nScree plot.nScree print.nScree summary.nScree
Utility Functions for nScree Class Objectsboxplot.structureSim is.structureSim plot.structureSim print.structureSim summary.structureSim