Creates a detailed summary of an EFA result. All sections are shown by
default; set individual toggles to FALSE to suppress specific sections.
Usage
# S3 method for class 'efa'
summary(
object,
kmo_bartlett = TRUE,
communalities = TRUE,
variance_explained = TRUE,
unrotated_matrix = TRUE,
rotated_matrix = TRUE,
pattern_matrix = TRUE,
structure_matrix = TRUE,
factor_correlations = TRUE,
digits = 3,
...
)Arguments
- object
An
efaresult object- kmo_bartlett
Show KMO and Bartlett's test? (Default: TRUE)
- communalities
Show communalities table? (Default: TRUE)
- variance_explained
Show total variance explained? (Default: TRUE)
- unrotated_matrix
Show unrotated component/factor matrix? (Default: TRUE)
- rotated_matrix
Show rotated matrix (varimax)? (Default: TRUE)
- pattern_matrix
Show pattern matrix (oblimin/promax)? (Default: TRUE)
- structure_matrix
Show structure matrix (oblimin/promax)? (Default: TRUE)
- factor_correlations
Show factor correlation matrix (oblimin/promax)? (Default: TRUE)
- digits
Number of decimal places (Default: 3)
- ...
Additional arguments (ignored)
See also
efa for the main analysis function.
Examples
result <- efa(survey_data, political_orientation, environmental_concern,
life_satisfaction, trust_government, trust_media, trust_science)
summary(result)
#>
#> Exploratory Factor Analysis (PCA, Varimax) Results
#> --------------------------------------------------
#> - Variables: political_orientation, environmental_concern, life_satisfaction, trust_government, trust_media, trust_science
#> - Extraction: Principal Component Analysis
#> - Rotation: Varimax with Kaiser Normalization
#> - N of Factors: 3
#>
#> KMO and Bartlett's Test
#> ----------------------------------------
#> Kaiser-Meyer-Olkin Measure: 0.505
#> Bartlett's Chi-Square: 932.068
#> df: 15
#> Sig.: 0.000
#>
#> Communalities
#> ----------------------------------------
#> variable initial extraction
#> political_orientation 1 0.786
#> environmental_concern 1 0.783
#> life_satisfaction 1 0.668
#> trust_government 1 0.347
#> trust_media 1 0.475
#> trust_science 1 0.598
#> Extraction Method: Principal Component Analysis.
#>
#> Total Variance Explained
#> ----------------------------------------
#> PC1 Eigenvalue: 1.600 Variance: 26.666% Cumulative: 26.666%
#> PC2 Eigenvalue: 1.041 Variance: 17.358% Cumulative: 44.024%
#> PC3 Eigenvalue: 1.017 Variance: 16.955% Cumulative: 60.979%
#> PC4 Eigenvalue: 0.980 Variance: 16.334% Cumulative: 77.313%
#> PC5 Eigenvalue: 0.949 Variance: 15.814% Cumulative: 93.127%
#> PC6 Eigenvalue: 0.412 Variance: 6.873% Cumulative: 100.000%
#>
#> Rotation Sums of Squared Loadings
#> ----------------------------------------
#> PC1 SS Loading: 1.598 Variance: 26.634% Cumulative: 26.634%
#> PC2 SS Loading: 1.039 Variance: 17.325% Cumulative: 43.959%
#> PC3 SS Loading: 1.021 Variance: 17.020% Cumulative: 60.979%
#>
#> Component Matrix (unrotated)
#> ----------------------------------------
#> PC1 PC2 PC3
#> political_orientation 0.885
#> environmental_concern -0.885
#> trust_science -0.672
#> trust_government -0.547
#> trust_media -0.524 -0.448
#> life_satisfaction -0.809
#> Extraction Method: Principal Component Analysis.
#>
#> Rotated Component Matrix
#> ----------------------------------------
#> PC1 PC2 PC3
#> political_orientation 0.887
#> environmental_concern -0.884
#> trust_science -0.762
#> trust_government -0.566
#> life_satisfaction -0.789
#> trust_media -0.620
#> Extraction Method: Principal Component Analysis.
#> Rotation Method: Varimax with Kaiser Normalization.
summary(result, communalities = FALSE)
#>
#> Exploratory Factor Analysis (PCA, Varimax) Results
#> --------------------------------------------------
#> - Variables: political_orientation, environmental_concern, life_satisfaction, trust_government, trust_media, trust_science
#> - Extraction: Principal Component Analysis
#> - Rotation: Varimax with Kaiser Normalization
#> - N of Factors: 3
#>
#> KMO and Bartlett's Test
#> ----------------------------------------
#> Kaiser-Meyer-Olkin Measure: 0.505
#> Bartlett's Chi-Square: 932.068
#> df: 15
#> Sig.: 0.000
#>
#> Total Variance Explained
#> ----------------------------------------
#> PC1 Eigenvalue: 1.600 Variance: 26.666% Cumulative: 26.666%
#> PC2 Eigenvalue: 1.041 Variance: 17.358% Cumulative: 44.024%
#> PC3 Eigenvalue: 1.017 Variance: 16.955% Cumulative: 60.979%
#> PC4 Eigenvalue: 0.980 Variance: 16.334% Cumulative: 77.313%
#> PC5 Eigenvalue: 0.949 Variance: 15.814% Cumulative: 93.127%
#> PC6 Eigenvalue: 0.412 Variance: 6.873% Cumulative: 100.000%
#>
#> Rotation Sums of Squared Loadings
#> ----------------------------------------
#> PC1 SS Loading: 1.598 Variance: 26.634% Cumulative: 26.634%
#> PC2 SS Loading: 1.039 Variance: 17.325% Cumulative: 43.959%
#> PC3 SS Loading: 1.021 Variance: 17.020% Cumulative: 60.979%
#>
#> Component Matrix (unrotated)
#> ----------------------------------------
#> PC1 PC2 PC3
#> political_orientation 0.885
#> environmental_concern -0.885
#> trust_science -0.672
#> trust_government -0.547
#> trust_media -0.524 -0.448
#> life_satisfaction -0.809
#> Extraction Method: Principal Component Analysis.
#>
#> Rotated Component Matrix
#> ----------------------------------------
#> PC1 PC2 PC3
#> political_orientation 0.887
#> environmental_concern -0.884
#> trust_science -0.762
#> trust_government -0.566
#> life_satisfaction -0.789
#> trust_media -0.620
#> Extraction Method: Principal Component Analysis.
#> Rotation Method: Varimax with Kaiser Normalization.