Podcast
Questions and Answers
According to the KMO and Bartlett's test results, is the dataset suitable for factor analysis?
According to the KMO and Bartlett's test results, is the dataset suitable for factor analysis?
- No, because the KMO value is below the acceptable threshold of 0.6.
- The results are inconclusive; additional tests are needed.
- Yes, because the Bartlett's test is significant (p < 0.05) and the KMO value is close to 0.8. (correct)
- No, because the degrees of freedom (df) is too high.
Based on the total variance explained table, how much of the total variance is explained by the first three components before rotation?
Based on the total variance explained table, how much of the total variance is explained by the first three components before rotation?
- 48.235% (correct)
- 37.578%
- 25.357%
- 63.964%
What criterion is used in the factor analysis to determine the number of components to extract?
What criterion is used in the factor analysis to determine the number of components to extract?
- Components with eigenvalues greater than 0.7.
- Components with eigenvalues greater than 1. (correct)
- Components that explain at least 10% of the variance.
- Components based on a scree plot visual inspection only.
What is the purpose of the ROTATION VARIMAX command in the provided SPSS syntax?
What is the purpose of the ROTATION VARIMAX command in the provided SPSS syntax?
In the context of factor analysis, what does the term 'communalities' refer to?
In the context of factor analysis, what does the term 'communalities' refer to?
Based on the Rotated Component Matrix, which variable loads highest on Component 1?
Based on the Rotated Component Matrix, which variable loads highest on Component 1?
Referring to the Component Transformation Matrix, what does this matrix describe?
Referring to the Component Transformation Matrix, what does this matrix describe?
How does the command /FORMAT BLANK (0.4) affect the output of the correlation matrix?
How does the command /FORMAT BLANK (0.4) affect the output of the correlation matrix?
What is the purpose of setting /MISSING LISTWISE in the SPSS syntax for factor analysis?
What is the purpose of setting /MISSING LISTWISE in the SPSS syntax for factor analysis?
If a variable has a communality of 0.8 after extraction, what does this indicate?
If a variable has a communality of 0.8 after extraction, what does this indicate?
Flashcards
Kaiser-Meyer-Olkin (KMO)
Kaiser-Meyer-Olkin (KMO)
A measure to determine the suitability of data for factor analysis. Values closer to 1 indicate the data is more suitable.
Bartlett's Test of Sphericity
Bartlett's Test of Sphericity
Tests the hypothesis that the correlation matrix is an identity matrix (i.e., variables are unrelated). A significant result suggests factor analysis is appropriate.
Communalities
Communalities
The proportion of variance in a variable explained by the extracted factors.
Initial Eigenvalues
Initial Eigenvalues
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Rotation Sums of Squared Loadings
Rotation Sums of Squared Loadings
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Scree Plot
Scree Plot
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Component Matrix
Component Matrix
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Rotated Component Matrix
Rotated Component Matrix
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Varimax Rotation
Varimax Rotation
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Component Transformation Matrix
Component Transformation Matrix
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Study Notes
- The data was obtained as an excel file called "Converted data.xlsx" containing a sheet named "Sheet1"
- Data type minimum percentage is 95.0
- Hidden files are ignored
Factor Analysis Variables
- The following variables are used in the factor analysis: PC1, PC2, PC4, Pc6, A1, A2, NC1, NC2, NC3, STN1, STN2, STN3, PHP1, PHP2, PHP3, PHP4.
- Missing data is handled by listwise deletion.
- The analysis includes printing the initial correlation matrix, significance levels, determinant, Kaiser-Meyer-Olkin (KMO) measure, inverse of the correlation matrix, reproduced correlations, Anti-image Correlation (AIC), extraction results, and rotation results.
- Values less than 0.4 are displayed as blank in the output.
- Eigenvalues greater than 1 are retained.
- Maximum of 25 iterations for extraction is allowed.
- Principal component extraction method is used.
- Maximum of 25 iterations for rotation is allowed.
- Varimax rotation method is used.
- Correlation matrix is the method.
KMO and Bartlett's Test
- Kaiser-Meyer-Olkin Measure of Sampling Adequacy is .741
- Bartlett's Test of Sphericity:
- Approx. Chi-Square: 708.078
- df: 120
- Sig.: .000
Communalities
- This table shows the initial and extraction communalities for each variable.
- Initial communalities are all 1.000.
- Extraction communalities range from .502 (Pc6) to .720 (NC1).
Total Variance Explained
- This table shows the initial eigenvalues, extraction sums of squared loadings, and rotation sums of squared loadings.
- 5 components have eigenvalues greater than 1.
- The 5 components explain 63.964% of the variance.
Component Matrix
- This table shows the component loadings for each variable on the unrotated components.
Rotated Component Matrix
- This table shows the component loadings for each variable on the rotated components using Varimax with Kaiser Normalization.
- Rotation converged in 7 iterations.
Component Transformation Matrix
- This table shows the component transformation matrix.
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