I think your approach is well-structured, especially your use of PCA with Varimax rotation and the clear criteria for retaining items. Linking the number of factors to both...
I think your approach is well-structured, especially your use of PCA with Varimax rotation and the clear criteria for retaining items. Linking the number of factors to both eigenvalues and theory is also a strong decision.
I do have a few questions though. First, since you’re using PCA, did you consider whether Exploratory Factor Analysis (e.g., Principal Axis Factoring) might be more appropriate for identifying underlying constructs rather than just data reduction? It could slightly change how the factors are interpreted.
Also, how will you handle items that load above .40 on more than one factor? Do you already have a rule (e.g., difference threshold) for deciding whether to keep or remove them?
Finally, I’m curious about your third factor—“challenges in using complex sentences.” Do you expect this to behave as a negative construct compared to the others? It might be interesting to check whether it correlates differently with the other factors.
I do have a few questions though. First, since you’re using PCA, did you consider whether Exploratory Factor Analysis (e.g., Principal Axis Factoring) might be more appropriate for identifying underlying constructs rather than just data reduction? It could slightly change how the factors are interpreted.
Also, how will you handle items that load above .40 on more than one factor? Do you already have a rule (e.g., difference threshold) for deciding whether to keep or remove them?
Finally, I’m curious about your third factor—“challenges in using complex sentences.” Do you expect this to behave as a negative construct compared to the others? It might be interesting to check whether it correlates differently with the other factors.