TY - JOUR
T1 - Investigating the role of orthogonal and non–orthogonal rotation in multivariate factor analysis, in regard to the repeatability of the extracted factors
T2 - A simulation study
AU - Panaretos, Dimitris
AU - Tzavelas, George
AU - Vamvakari, Malvina
AU - Panagiotakos, Demosthenes
N1 - Funding Information:
Dimitris Panaretos has received a scholarship by ELIDEK/Ministry of Education for the completion of his PhD studies (2017-2019).
Publisher Copyright:
© 2018, © 2018 Taylor & Francis Group, LLC.
PY - 2019/8/9
Y1 - 2019/8/9
N2 - 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.
AB - 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.
KW - Factor analysis
KW - multivariate analysis
KW - recognition pattern analysis
KW - repeatability
KW - rotation
UR - http://www.scopus.com/inward/record.url?scp=85042221391&partnerID=8YFLogxK
U2 - 10.1080/03610918.2018.1435803
DO - 10.1080/03610918.2018.1435803
M3 - Article
AN - SCOPUS:85042221391
SN - 0361-0918
VL - 48
SP - 2165
EP - 2176
JO - Communications in Statistics: Simulation and Computation
JF - Communications in Statistics: Simulation and Computation
IS - 7
ER -