Investigating the role of orthogonal and non – orthogonal rotation in multivariate factor analysis, in regard to the repeatability of the extracted factors: A simulation study

ABSTRACT

Factor analysis (FA) is the most commonly used pattern recognition methodology in social and health research. A technique that may help to better retrieve true information from FA is the rotation of the information axes. The main goal is to test the reliability of the results derived through FA and to reveal the best rotation method under various scenarios. Based on the results of the simulations, it was observed that when applying non-orthogonal rotation, the results were more repeatable as compared to the orthogonal rotation, and, when no rotation was applied.

KEYWORDS:

• Factor analysis
• multivariate analysis
• recognition pattern analysis
• rotation
• repeatability

Conflict of interest

None to declare

Additional information

Funding

Dimitris Panaretos has received a scholarship by ELIDEK/Ministry of Education for the completion of his PhD studies (2017-2019).