| Summary: | 碩士 === 國立中正大學 === 心理學研究所 === 100 === Traditionally, in second-order factor analysis, the first-order factors are extracted and such factors are subsequently regarded as new observed variables so second- order factors are extracted. Since the second-order factors are determined by the first-order ones, the conventional two-staged method will cause problems if the preselection for the first-order factors is inappropriate.
An intuitive way to solve the problem is, when extracting the first-order factors, to evaluate its effect upon the second -order ones. Specifically, we’d like to define a new rotation criterion to assess the performance for both pattern matrices simultaneously. Such estimation process is hence reduced to a one-staged method.
To testify the efficiency of such criterion, we analyzed three simulated and one real datasets, then compared the results between the two-staged and one-staged methods. The results showed that the proposed method performed better when the first-order pattern matrix is complex but worse when so is the second-order pattern matrix. The proposed method can also apply to other rotation criteria. Besides, assumption about the correct numbers of first- and second-order factors is not always the case. A future research for determining the numbers of these factors is needed.
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