Section author: Ravi Selker, Jonathon Love, Damian Dropmann
Exploratory Factor Analysis (efa)
Description
Exploratory Factor Analysis
Usage
efa(
data,
vars,
nFactorMethod = "parallel",
nFactors = 1,
minEigen = 1,
extraction = "minres",
rotation = "oblimin",
hideLoadings = 0.3,
sortLoadings = FALSE,
screePlot = FALSE,
eigen = FALSE,
factorCor = FALSE,
factorSummary = FALSE,
modelFit = FALSE,
kmo = FALSE,
bartlett = FALSE
)
Arguments
|
the data as a data frame |
|
a vector of strings naming the variables of
interest in |
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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 |
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a number (default: 0.3), hide factor loadings below this value |
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Output
A results object containing:
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a preformatted |
Examples
data('iris')
efa(iris, vars = vars(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width))
#
# EXPLORATORY FACTOR ANALYSIS
#
# 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
#