Rotation Criteria and Hypothesis Testing for Exploratory Factor Analysis: Implications for Factor Pattern Loadings and Interfactor Correlations

Educational and Psychological Measurement - Tập 71 Số 1 - Trang 95-113 - 2011
Thomas A. Schmitt1, Daniel A. Sass2
1Eastern Michigan University, Ypsilanti, MI, USA#TAB#
2University of Texas at San Antonio, San Antonio, TX, USA

Tóm tắt

Exploratory factor analysis (EFA) has long been used in the social sciences to depict the relationships between variables/items and latent traits. Researchers face many choices when using EFA, including the choice of rotation criterion, which can be difficult given that few research articles have discussed and/or demonstrated their differences. The goal of the current study is to help fill this gap by reviewing and demonstrating the utility of several rotation criteria. Furthermore, this article discusses and demonstrates the importance of using factor pattern loading standard errors for hypothesis testing. The choice of a rotation criterion and the use of standard errors in evaluating factor loadings are essential so researchers can make informed decisions concerning the factor structure. This study demonstrates that depending on the rotation criterion selected, and the complexity of the factor pattern matrix, the interfactor correlations and factor pattern loadings can vary substantially. It is also illustrated that the magnitude of the factor loading standard errors can result in different factor structures. Implications and future directions are discussed.

Từ khóa


Tài liệu tham khảo

10.1080/10705510903008204

10.1207/S15327906MBR3601_05

10.1007/BF02289025

10.1037/h0025178

10.1007/BF02289594

Comrey, A.L., 1992, A first course in factor analysis

10.1037/h0076374

10.1007/BF02310792

10.1177/0146167294206001

10.1037/0033-2909.115.3.475

10.1037/1082-989X.4.3.272

10.1111/j.1744-6570.1986.tb00583.x

Gorsuch, R.L., 1983, Factor analysis, 2

10.1111/j.2044-8317.1964.tb00244.x

10.1177/0013164405282485

10.1007/s11336-003-1136-B

Jennrich, R.I. ( 2007). Rotation methods, algorithms, and standard errors. In R. Cudeck & R. C. MacCallum (Eds.), Factor analysis at 100: Historical developments and future directions (1st ed., pp. 315-335). Mahwah, NJ: Erlbaum.

10.1007/BF02289233

10.1037/0033-2909.111.3.490

10.1080/10705510903008220

10.1207/s15328007sem1201_9

McLeod, L.D., Swygert, K.A. & Thissen, D. ( 2001). Factor analysis for items scored in two categories. In D. Thissen & H. Wainer (Eds), Test scoring (pp. 189-216). Mahwah, NJ: Erlbaum.

Mulaik, S.A. ( 2005). Looking back on the indeterminacy controversies in factor analysis. In A. Maydeu-Olivares & J. J. McArdle (Eds.), Contemporary psychometrics: A festschrift for Roderick P. McDonald (pp. 173-206). Mahwah, NJ : Erlbaum.

Muthén, L.K., 1998, Mplus user’s guide

10.2333/bhmk.27.1

10.1007/BF02290161

Sass, D.A., 2010, Multivariate Behavioral Research, 45, 1, 10.1080/00273170903504695

Thurstone, L.L., 1947, Multiple-factor analysis

Yates, A., 1987, Multivariate exploratory data analysis: A perspective on exploratory factor analysis

Thông tin
Thông tin xuất bản

Educational and Psychological Measurement

Tập 71 Số 1

95-113

Thông tin tác giả