
Exploratory Factor Analysis
efa(data, vars, nFactorMethod = "parallel", nFactors = 1, minEigen = 1,
rotation = "oblimin", hideLoadings = 0.3, screePlot = FALSE,
eigen = FALSE, factorCor = FALSE, factorSummary = FALSE,
modelFit = FALSE, kmo = FALSE, bartlett = FALSE)
the data as a data frame
a vector of strings naming the variables of interest in
data
'parallel'
(default), 'eigen'
or
'fixed'
, the way to determine the number of factors
an integer (default: 1), the number of factors in the model
a number (default: 1), the minimal eigenvalue for a factor to be included in the model
'none'
, 'varimax'
(default),
'quartimax'
, 'promax'
, 'oblimin'
, or
'simplimax'
, the rotation to use in estimation
a number (default: 0.3), hide loadings below this value
TRUE
or FALSE
(default), show scree plot
TRUE
or FALSE
(default), show eigenvalue table
TRUE
or FALSE
(default), show factor
correlations
TRUE
or FALSE
(default), show factor
summary
TRUE
or FALSE
(default), show model fit
measures and test
TRUE
or FALSE
(default), show Kaiser-Meyer-Olkin
(KMO) measure of sampling adequacy (MSA) results
TRUE
or FALSE
(default), show Bartlett's test
of sphericity results
data('iris')
efa(iris, vars = c('Sepal.Length', 'Sepal.Width', 'Petal.Length', 'Petal.Width'))
#
# Factor Loadings
# ------------------------------------------------
# 1 2 Uniqueness
# ------------------------------------------------
# Sepal.Length 0.993 0.10181
# Sepal.Width 0.725 0.42199
# Petal.Length 0.933 0.00483
# Petal.Width 0.897 0.07088
# ------------------------------------------------
# Note. 'oblimin' rotation was used
#
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