Fast and Flexible Implementations of Exploratory Factor Analysis
Tools
c(person(given = "Markus",
family = "Steiner",
role = c("aut", "cre"),
email = "markus.d.steiner@gmail.com"),
person(given = "Silvia",
family = "Grieder",
role = "aut",
email = "silvia.grieder@gmail.com"),
person(given = "William",
family = "Revelle",
role = "ctb"),
person(given = "Max",
family = "Auerswald",
role = "ctb"),
person(given = "Morten",
family = "Moshagen",
role = "ctb"),
person(given = "John",
family = "Ruscio",
role = "ctb"),
person(given = "Brendan",
family = "Roche",
role = "ctb"),
person(given = "Urbano",
family = "Lorenzo-Seva",
role = "ctb"),
person(given = "David",
family = "Navarro-Gonzalez",
role = "ctb"))
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++.
lavaan, psych, crayon, stringr, stats, ggplot2, plotly,
tibble, magrittr, dplyr, cli, Rcpp, viridisLite, graphics,
parallel, future.apply, future, GPArotation, checkmate,
microbenchmark
Markus Steiner [aut, cre],
Silvia Grieder [aut],
William Revelle [ctb],
Max Auerswald [ctb],
Morten Moshagen [ctb],
John Ruscio [ctb],
Brendan Roche [ctb],
Urbano Lorenzo-Seva [ctb],
David Navarro-Gonzalez [ctb]

lavaan, psych, crayon, stringr, stats, ggplot2, tibble,
magrittr, dplyr, cli, Rcpp, viridisLite, graphics,
future.apply, future, GPArotation, checkmate

lavaan, psych, crayon, stringr, stats, ggplot2, tibble,
magrittr, dplyr, cli, Rcpp, viridisLite, graphics,
future.apply, future, GPArotation, checkmate, tidyr, progressr,
progress, rlang

Utility Functions for Exploratory Factor Analysis
Guangjian Zhang, Ge Jiang, Minami Hattori, Lauren Trichtinger
A number of utility function for exploratory
factor analysis are included in this package. In particular, it computes standard errors for parameter estimates and factor correlations under a variety of conditions.