Exploratory Factor Analysis

Exploratory Factor Analysis

Example usage


efa(iris, vars = vars(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


data the data as a data frame
vars a vector of strings naming the variables of interest in data
nFactorMethod 'parallel' (default), 'eigen' or 'fixed', the way to determine the number of factors
nFactors an integer (default: 1), the number of factors in the model
minEigen a number (default: 1), the minimal eigenvalue for a factor to be included in the model
extraction 'minres' (default), 'ml', or 'pa' use respectively 'minimum residual', 'maximum likelihood', or 'prinicipal axis' as the factor extraction method
rotation 'none', 'varimax', 'quartimax', 'promax', 'oblimin' (default), or 'simplimax', the rotation to use in estimation
hideLoadings a number (default: 0.3), hide factor loadings below this value
sortLoadings TRUE or FALSE (default), sort the factor loadings by size
screePlot TRUE or FALSE (default), show scree plot
eigen TRUE or FALSE (default), show eigenvalue table
factorCor TRUE or FALSE (default), show factor correlations
factorSummary TRUE or FALSE (default), show factor summary
modelFit TRUE or FALSE (default), show model fit measures and test
kmo TRUE or FALSE (default), show Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (MSA) results
bartlett TRUE or FALSE (default), show Bartlett's test of sphericity results


A results object containing: