1. Determine whether to use EFA or PCA? - What are the underlying assumptions of EFA?

1. Determine whether to use EFA or PCA? - What are the underlying assumptions of EFA? - What are the underlying assumptions of PCA? - What is relevant to your research questions/hypotheses? 2. Determine which model estimation/ extraction method to use? - List the different estimation/ extraction methods (e.g., Maximum Likelihood etc). - What are the advantages and disadvantages of each method? - What is relevant to your research questions/hypotheses? 3. How many factors to retain? - List the different procedures to determine the number of factors to retain (e.g., Kaiser’s criterion). - What are the advantages and disadvantages of each method? - What is relevant to your research questions/hypotheses? 4. Which factor rotation should be used? - What are the underlying assumptions of orthogonal rotation? - What are the underlying assumptions of oblique rotation? - What is relevant to your research questions/hypotheses? 5. What criteria will be used for retaining/deleting items? - What is the minimum strength of the factor loadings that will be retained? - What is the minimum number of items per factor that will be used to interpret a factor? - How will items that cross-load be addressed?  



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