HUF04 - Vo Dao Trang Thy

HUF04 - Vo Dao Trang Thy

by HUF04 Vo Dao Trang Thy -

For my EFA, I used principal component analysis as the extraction method and Varimax rotation. The KMO value was .893, and Bartlett’s test was significant, χ²(153) = 3110....

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For my EFA, I used principal component analysis as the extraction method and Varimax rotation. The KMO value was .893, and Bartlett’s test was significant, χ²(153) = 3110.484, p < .001, which showed that the data were suitable for factor analysis.

In total, 18 items were included in the analysis, and 4 factors were retained because they had eigenvalues greater than 1. This result was slightly different from my original expectation of 3 constructs. The Life Satisfaction items grouped together clearly, while the Optimism and Mastery items showed a more mixed pattern. Most items were retained, but one Optimism item showed cross-loading, so it may need more careful interpretation.

by HUF04 Vo Dao Trang Thy -
Number of replies: 3

HUF04 - Vo Dao Trang Thy

by HUF04 Trần Huỳnh Gia Hân -
Your EFA results are well presented, and the high KMO (.893) strongly supports the suitability of your data. It’s also good that you clearly explained why four factors were...

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Your EFA results are well presented, and the high KMO (.893) strongly supports the suitability of your data. It’s also good that you clearly explained why four factors were retained. I’m curious about your decision to rely on the eigenvalue > 1 rule—did you also check the scree plot to confirm the number of factors? Sometimes it can suggest a different structure. Also, since the Mastery items were split, do you think this construct might actually consist of two sub-dimensions rather than one? It could be interesting to explore that further or compare it with the original scale.
In reply to HUF04 Vo Dao Trang Thy
by HUF04 Trần Huỳnh Gia Hân -

HUF04 - Vo Dao Trang Thy

by HUF04 Võ Thị Bích Hạnh -
Your EFA report is clear and shows good understanding of the analysis. You correctly reported KMO and Bartlett’s test, and your interpretation of factor retention based on ...

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Your EFA report is clear and shows good understanding of the analysis. You correctly reported KMO and Bartlett’s test, and your interpretation of factor retention based on eigenvalues is appropriate. The discussion of cross-loading is also thoughtful.

To improve, you could briefly explain why PCA was chosen instead of common factor analysis (e.g., PAF). Also, clarify whether you considered the scree plot or theoretical meaning when deciding on 4 factors. Finally, you might suggest whether to remove or revise the cross-loading item.
In reply to HUF04 Trần Huỳnh Gia Hân
by HUF04 Võ Thị Bích Hạnh -

HUF04 - Vo Dao Trang Thy

by HUF04 Hoàng Phan Trung Hiếu -
Your EFA results are clearly presented and easy to understand. I think your choice of extraction and rotation methods is appropriate. However, I’m curious about how you ...

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Your EFA results are clearly presented and easy to understand. I think your choice of extraction and rotation methods is appropriate. However, I’m curious about how you decided on the number of factors. Did you rely only on eigenvalues, or did you also consider the scree plot? This might help strengthen your justification.
In reply to HUF04 Vo Dao Trang Thy
by HUF04 Hoàng Phan Trung Hiếu -