run_efa: Conducts exploratory factor analysis

View source: R/run_efa.R

run_efaR Documentation

Conducts exploratory factor analysis

Description

This function is intended for use on independent samples rather than integrated with k-fold cross-validation.

Usage

run_efa(
  variables,
  m = floor(ncol(variables)/4),
  rotation = "oblimin",
  simple = TRUE,
  threshold = NA,
  single.item = c("keep", "drop", "none"),
  identified = TRUE,
  constrain0 = FALSE,
  ordered = FALSE,
  estimator = NULL,
  missing = "listwise",
  ...
)

Arguments

variables

a data.frame (or convertible to a data.frame) of variables (i.e., items) to factor analyze

m

integer; maximum number of factors to extract. Default is 4 items per factor.

rotation

character (case-sensitive); any rotation method listed in rotations in the GPArotation package. Default is "oblimin".

simple

logical; Should the most simple structure be returned (default)? If FALSE, items can cross load on multiple factors.

threshold

numeric between 0 and 1 indicating the minimum (absolute) value of the loading for an item on a factor.

single.item

character indicating how single-item factors should be treated. Use "keep" (default) to keep them in the model when generating the CFA syntax, "drop" to remove them, or "none" indicating the CFA syntax should not be generated for this model and "" will be returned.

identified

logical; Should identification check for rotational uniqueness a la Millsap (2001) be performed?

constrain0

logical; Should variable(s) with all loadings below threshold still be included in model syntax? If TRUE, variable(s) will load onto first factor with the loading constrained to 0.

ordered

logical; Should items be treated as ordinal and the polychoric correlations used in the factor analysis? When FALSE (default) the Pearson correlation matrix is used. A character vector of item names is also accepted to prompt estimation of the polychoric correlation matrix.

estimator

if ordered = FALSE, the default is "ML". If ordered = TRUE, the default is "DWLS". See lavaan for other options.

missing

default is "listwise". See lavaan for other options.

...

other arguments passed to lavaan functions. See lavOptions.

Value

A three-element list:

  • efas lavaan object for each m model

  • loadings (rotated) factor loading matrix for each m model

  • cfa.syntax CFA syntax generated from loadings

Examples


# simulate data based on a 3-factor model with standardized loadings
sim.mod <- "f1 =~ .7*x1 + .8*x2 + .3*x3 + .7*x4 + .6*x5 + .8*x6 + .4*x7
                f2 =~ .8*x8 + .7*x9 + .6*x10 + .5*x11 + .5*x12 + .7*x13 + .6*x14
                f3 =~ .6*x15 + .5*x16 + .9*x17 + .4*x18 + .7*x19 + .5*x20
                f1 ~~ .2*f2
                f2 ~~ .2*f3
                f1 ~~ .2*f3
                x9 ~~ .2*x10"
set.seed(1161)
sim.data <- simstandard::sim_standardized(sim.mod, n = 900,
                                          latent = FALSE,
                                          errors = FALSE)[c(2:9,1,10:20)]
# Run 1-, 2-, and 3-factor models
efas <- run_efa(sim.data, m = 3)


kfa documentation built on March 18, 2022, 5:26 p.m.

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