The authors would like to make the following corrections to [1]. The changes are as follows:
- (1)
- One sentence in Section 5.2, “Reliability Testing” should be deleted.
The deleted part is as follows:
- Following Weaver and Maxwell [121], the Varimax rotation method was selected for this study.
- (2)
- The following reference should be removed from the citation list:
121. Weaver, B.; Maxwell, H. (PDF) Exploratory Factor Analysis and Reliability Analysis with Missing Data: A Simple Method for SPSS Users. Quant. Methods Psychol. 2014, 10, 143–152. https://doi.org/10.20982/tqmp.10.2.p143.
- (3)
- To clearly indicate the data analysis methods, the authors wish to add an explanation along with references in Section 5.2, “Reliability Testing”.
The following is the original version:
Based on the recommendations of Hair et al. [118], items with loadings below 0.7 should be excluded from future analyses. Consequently, only the items in bold (with loadings greater than 0.7) in Appendix A have been retained in the final results.
The replacement is as follows:
The Varimax rotation method was chosen for this study with the aim of maximizing the variance of the squared loadings within each factor, which can help simplify the factor structure and improve interpretability [121]. This method is often seen as useful for identifying distinct factors with clear loadings as it tends to maximize the variance of the squared loadings in each factor column [122]. In this way, we obtain clear and more easily interpretable results [123,124]. Based on the recommendations of Hair et al. [118], items with loadings below 0.7 should be excluded from future analyses. Consequently, only the items in bold (with loadings greater than 0.7) in Appendix A have been retained in the final results.
- (4)
- The following references should be added to the citation list:
121. Kaiser, H.F. The varimax criterion for analytic rotation in factor analysis. Psychometrika 1958, 23, 187–200.
122. Costello, A.B.; Osborne, J. Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pract. Assess. Res. Eval. 2005, 10, 7.
123. Wang, H.; Liu, Q.; Tu, Y. Interpretation of partial least-squares regression models with VARIMAX rotation. Comput. Stat. Data Anal. 2005, 48, 207–219.
124. Han, R.; Zhang, A.R. Rungang Han and Anru R. Zhangs contribution to the Discussion of ‘Vintage factor analysis with varimax performs statistical inference’ by Rohe & Zeng. J. R. Stat. Soc. Ser. B Stat. Methodol. 2023, 85, 1069–1070.
With this correction, the order of some references has been adjusted accordingly. The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.
Reference
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