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Behavior Research Methods

, Volume 42, Issue 3, pp 871–876 | Cite as

Estimating confidence intervals for eigenvalues in exploratory factor analysis

  • Ross LarsenEmail author
  • Russell T. Warne
Article

Abstract

Exploratory factor analysis (EFA) has become a common procedure in educational and psychological research. In the course of performing an EFA, researchers often base the decision of how many factors to retain on the eigenvalues for the factors. However, many researchers do not realize that eigenvalues, like all sample statistics, are subject to sampling error, which means that confidence intervals (CIs) can be estimated for each eigenvalue. In the present article, we demonstrate two methods of estimating CIs for eigenvalues: one based on the mathematical properties of the central limit theorem, and the other based on bootstrapping. References to appropriate SAS and SPSS syntax are included. Supplemental materials for this article may be downloaded from http://brm.psychonomic-journals.org/content/supplemental.

Keywords

Exploratory Factor Analysis Central Limit Theorem American Psychological Association Parallel Analysis Estimate Confidence Interval 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material

Larsen-BRM-2010.zip (12 kb)
Supplementary material, approximately 340 KB.

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Copyright information

© Psychonomic Society, Inc. 2010

Authors and Affiliations

  1. 1.Department of Educational PsychologyTexas A&M University, TAMU 4225College Station

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