Replication Analysis in Exploratory Factor Analysis: What it is and why it makes your analysis better
DOI
https://doi.org/10.7275/h0bd-4d11
Abstract
Exploratory Factor Analysis (EFA) is a powerful and commonly-used tool for investigating the underlying variable structure of a psychometric instrument. However, there is much controversy in the social sciences with regard to the techniques used in EFA (Ford, MacCallum, & Tait, 1986; Henson & Roberts, 2006) and the reliability of the outcome. Simulations by Costello and Osborne (2005), for example, demonstrate how poorly some EFA analyses replicate, even with clear underlying factor structures and large samples. Thus, we argue that researchers should routinely examine the stability or volatility of their EFA solutions to gain more insight into the robustness of their solutions and insight into how to improve their instruments while still at the exploratory stage of development. Accessed 13,498 times on https://pareonline.net from November 01, 2012 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Osborne, Jason W. and Fitzpatrick, David C.
(2019)
"Replication Analysis in Exploratory Factor Analysis: What it is and why it makes your analysis better,"
Practical Assessment, Research, and Evaluation: Vol. 17, Article 15.
DOI: https://doi.org/10.7275/h0bd-4d11
Available at:
https://scholarworks.umass.edu/pare/vol17/iss1/15