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,
descriptives = 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)
- descriptives
Show the per-item descriptive statistics (mean, SD, analysis N, missing N; SPSS
/PRINT UNIVARIATE)? (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 Political orientation (1=left, 5=right)
#> environmental_concern Environmental concern (1=low, 5=high)
#> life_satisfaction Life satisfaction (1=dissatisfied, 5=satisfied)
#> trust_government Trust in government (1=none, 5=complete)
#> trust_media Trust in media (1=none, 5=complete)
#> trust_science Trust in science (1=none, 5=complete)
#> - Extraction: Principal Component Analysis
#> - Rotation: Varimax with Kaiser Normalization
#> - N of Components: 3
#> - N (smallest pairwise): 2168
#>
#> Descriptive Statistics
#> -------------------------------------------------------------------
#> Variable Mean Std. Deviation Analysis N Missing N
#> -------------------------------------------------------------------
#> political_orientation 2.722 1.086 2299 201
#> environmental_concern 3.573 1.194 2400 100
#> life_satisfaction 3.628 1.153 2421 79
#> trust_government 2.621 1.163 2354 146
#> trust_media 2.452 1.163 2367 133
#> trust_science 3.641 1.028 2398 102
#> -------------------------------------------------------------------
#>
#> KMO and Bartlett's Test
#> ----------------------------------------
#> Kaiser-Meyer-Olkin Measure: 0.505
#> Bartlett's Chi-Square: 932.068
#> df: 15
#> Sig.: <.001
#>
#> Communalities
#> ---------------------------------------------------------------------
#> Variable Initial Extraction
#> ---------------------------------------------------------------------
#> political_orientation Political orientation ... 1.000 0.786
#> environmental_concern Environmental concern ... 1.000 0.783
#> life_satisfaction Life satisfaction (1=d... 1.000 0.668
#> trust_government Trust in government (1... 1.000 0.347
#> trust_media Trust in media (1=none... 1.000 0.475
#> trust_science Trust in science (1=no... 1.000 0.598
#> ---------------------------------------------------------------------
#> Extraction Method: Principal Component Analysis.
#>
#> Total Variance Explained
#> -------------------------------------------------------------------------
#> Initial Eigenvalues Extraction Sums Rotation Sums
#> Component Total % Var. Cum. % Total % Var. Cum. % Total % Var. Cum. %
#> -------------------------------------------------------------------------
#> 1 1.600 26.666 26.666 1.600 26.666 26.666 1.598 26.635 26.635
#> 2 1.041 17.358 44.024 1.041 17.358 44.024 1.039 17.324 43.959
#> 3 1.017 16.955 60.979 1.017 16.955 60.979 1.021 17.020 60.979
#> 4 0.980 16.334 77.313
#> 5 0.949 15.814 93.127
#> 6 0.412 6.873 100.000
#> -------------------------------------------------------------------------
#> Sums = sums of squared loadings.
#> Extraction Method: Principal Component Analysis.
#>
#> Component Matrix (unrotated)
#> ----------------------------------------
#> PC1 PC2 PC3
#> political_orientation Political orientation (1=lef... -0.885
#> environmental_concern Environmental concern (1=low... 0.885
#> trust_science Trust in science (1=none, 5=... 0.672
#> trust_government Trust in government (1=none,... 0.547
#> trust_media Trust in media (1=none, 5=co... 0.524 0.448
#> life_satisfaction Life satisfaction (1=dissati... 0.809
#> Extraction Method: Principal Component Analysis.
#>
#> Rotated Component Matrix
#> ----------------------------------------
#> PC1 PC2 PC3
#> political_orientation Political orientation (1=lef... -0.887
#> environmental_concern Environmental concern (1=low... 0.884
#> trust_science Trust in science (1=none, 5=... 0.762
#> trust_government Trust in government (1=none,... 0.566
#> life_satisfaction Life satisfaction (1=dissati... 0.789
#> trust_media Trust in media (1=none, 5=co... 0.620
#> Extraction Method: Principal Component Analysis.
#> Rotation Method: Varimax with Kaiser Normalization.
#> Rotation converged in 4 iterations.
summary(result, communalities = FALSE)
#>
#> Exploratory Factor Analysis (PCA, Varimax) Results
#> --------------------------------------------------
#> - Variables:
#> political_orientation Political orientation (1=left, 5=right)
#> environmental_concern Environmental concern (1=low, 5=high)
#> life_satisfaction Life satisfaction (1=dissatisfied, 5=satisfied)
#> trust_government Trust in government (1=none, 5=complete)
#> trust_media Trust in media (1=none, 5=complete)
#> trust_science Trust in science (1=none, 5=complete)
#> - Extraction: Principal Component Analysis
#> - Rotation: Varimax with Kaiser Normalization
#> - N of Components: 3
#> - N (smallest pairwise): 2168
#>
#> Descriptive Statistics
#> -------------------------------------------------------------------
#> Variable Mean Std. Deviation Analysis N Missing N
#> -------------------------------------------------------------------
#> political_orientation 2.722 1.086 2299 201
#> environmental_concern 3.573 1.194 2400 100
#> life_satisfaction 3.628 1.153 2421 79
#> trust_government 2.621 1.163 2354 146
#> trust_media 2.452 1.163 2367 133
#> trust_science 3.641 1.028 2398 102
#> -------------------------------------------------------------------
#>
#> KMO and Bartlett's Test
#> ----------------------------------------
#> Kaiser-Meyer-Olkin Measure: 0.505
#> Bartlett's Chi-Square: 932.068
#> df: 15
#> Sig.: <.001
#>
#> Total Variance Explained
#> -------------------------------------------------------------------------
#> Initial Eigenvalues Extraction Sums Rotation Sums
#> Component Total % Var. Cum. % Total % Var. Cum. % Total % Var. Cum. %
#> -------------------------------------------------------------------------
#> 1 1.600 26.666 26.666 1.600 26.666 26.666 1.598 26.635 26.635
#> 2 1.041 17.358 44.024 1.041 17.358 44.024 1.039 17.324 43.959
#> 3 1.017 16.955 60.979 1.017 16.955 60.979 1.021 17.020 60.979
#> 4 0.980 16.334 77.313
#> 5 0.949 15.814 93.127
#> 6 0.412 6.873 100.000
#> -------------------------------------------------------------------------
#> Sums = sums of squared loadings.
#> Extraction Method: Principal Component Analysis.
#>
#> Component Matrix (unrotated)
#> ----------------------------------------
#> PC1 PC2 PC3
#> political_orientation Political orientation (1=lef... -0.885
#> environmental_concern Environmental concern (1=low... 0.885
#> trust_science Trust in science (1=none, 5=... 0.672
#> trust_government Trust in government (1=none,... 0.547
#> trust_media Trust in media (1=none, 5=co... 0.524 0.448
#> life_satisfaction Life satisfaction (1=dissati... 0.809
#> Extraction Method: Principal Component Analysis.
#>
#> Rotated Component Matrix
#> ----------------------------------------
#> PC1 PC2 PC3
#> political_orientation Political orientation (1=lef... -0.887
#> environmental_concern Environmental concern (1=low... 0.884
#> trust_science Trust in science (1=none, 5=... 0.762
#> trust_government Trust in government (1=none,... 0.566
#> life_satisfaction Life satisfaction (1=dissati... 0.789
#> trust_media Trust in media (1=none, 5=co... 0.620
#> Extraction Method: Principal Component Analysis.
#> Rotation Method: Varimax with Kaiser Normalization.
#> Rotation converged in 4 iterations.