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Factor analysis is a multivariate statistical method widely used in social indicator analysis. Most of time, factor analysis results in the textbook only give some mathematical expressions without clear interpretation. Motivated from a case study on a popular textbook, this paper attempts to illustrate the potential pitfall of factor analysis in some real applications. The study demonstrates that without careful examination of the original dataset, factor analysis can lead to misleading conclusions. This issue has been largely ignored in the literature including popular textbooks. The statistical analysis cannot completely rely on the automated computer software. The Kaiser-Meyer-Olkin (KMO) test results can only be used as a reference. We should carefully examine the applicability of the original data and give a cautious explanation. Provided that some popular textbooks ignore this point, we wish this article can draw the readers' special attention to the raw data when conducting factor analysis.
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