EFAtools0.6.1 package

Fast and Flexible Implementations of Exploratory Factor Analysis Tools

BARTLETT

Bartlett's test of sphericity

CD

Comparison Data

COMPARE

Compare two vectors or matrices (communalities or loadings)

dot-compute_vars

Compute explained variances from loadings

dot-factor_corres

Compute number of non-matching indicator-to-factor correspondences

dot-nest_sym

Get reference values for nest.

dot-numformat

Format numbers for print method

dot-paf_iter

Perform the iterative PAF procedure

dot-parallel_sim

Parallel analysis on simulated data.

EFA_AVERAGE

Model averaging across different EFA methods and types

EFA

Exploratory factor analysis (EFA)

EFAtools-package

EFAtools: Fast and Flexible Implementations of Exploratory Factor Anal...

EKC

Empirical Kaiser Criterion

FACTOR_SCORES

Estimate factor scores for an EFA model

HULL

Hull method for determining the number of factors to retain

KGC

Kaiser-Guttman Criterion

KMO

Kaiser-Meyer-Olkin criterion

N_FACTORS

Various Factor Retention Criteria

NEST

Next eigenvalue sufficiency test (NEST)

OMEGA

McDonald's omega

PARALLEL

Parallel analysis

pipe

Pipe operator

plot.CD

Plot CD object

plot.EFA_AVERAGE

Plot EFA_AVERAGE object

plot.EKC

Plot EKC object

plot.HULL

Plot HULL object

plot.KGC

Plot KGC object

plot.PARALLEL

Plot PARALLEL object

plot.SCREE

Plot SCREE object

print.BARTLETT

Print BARTLETT object

print.CD

Print function for CD objects

print.COMPARE

Print COMPARE object

print.EFA_AVERAGE

Print EFA_AVERAGE object

print.EFA

Print EFA object

print.EKC

Print function for EKC objects

print.HULL

Print function for HULL objects

print.KGC

Print function for KGC objects

print.KMO

Print KMO object

print.LOADINGS

Print LOADINGS object

print.N_FACTORS

Print function for N_FACTORS objects

print.NEST

Print function for NEST objects

print.OMEGA

Print OMEGA object

print.PARALLEL

Print function for PARALLEL objects

print.SCREE

Print function for SCREE objects

print.SL

Print SL object

print.SLLOADINGS

Print SLLOADINGS object

print.SMT

Print SMT object

SCREE

Scree Plot

SL

Schmid-Leiman Transformation

SMT

Sequential Chi Square Model Tests, RMSEA lower bound, and AIC

Provides functions to perform exploratory factor analysis (EFA) procedures and compare their solutions. The goal is to provide state-of-the-art factor retention methods and a high degree of flexibility in the EFA procedures. This way, for example, implementations from R 'psych' and 'SPSS' can be compared. Moreover, functions for Schmid-Leiman transformation and the computation of omegas are provided. To speed up the analyses, some of the iterative procedures, like principal axis factoring (PAF), are implemented in C++.

  • Maintainer: Markus Steiner
  • License: GPL-3
  • Last published: 2025-07-30