Skip to main content
Log in

Exploratory Bi-Factor Analysis

  • Published:
Psychometrika Aims and scope Submit manuscript

An Erratum to this article was published on 01 June 2013

Abstract

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger. The bi-factor model has a general factor and a number of group factors. The purpose of this article is to introduce an exploratory form of bi-factor analysis. An advantage of using exploratory bi-factor analysis is that one need not provide a specific bi-factor model a priori. The result of an exploratory bi-factor analysis, however, can be used as an aid in defining a specific bi-factor model. Our exploratory bi-factor analysis is simply exploratory factor analysis using a bi-factor rotation criterion. This is a criterion designed to approximate perfect cluster structure in all but the first column of a rotated loading matrix. Examples are given to show how exploratory bi-factor analysis can be used with ideal and real data. The relation of exploratory bi-factor analysis to the Schmid–Leiman method is discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Bernaards, C.A., & Jennrich, R.I. (2003). Orthomax rotation and perfect simple structure. Psychometrika, 68, 585–588.

    Article  Google Scholar 

  • Chen, F.F., West, S.G., & Sousa, K.H. (2006). A comparison of bifactor and second-order models of the quality of life. Multivariate Behavioral Research, 41, 189–225.

    Article  Google Scholar 

  • Harman, H.H. (1976). Modern factor analysis (3rd ed.). Chicago: The University of Chicago Press.

    Google Scholar 

  • Holzinger, K.J., & Swineford, S. (1937). The Bi-factor method. Psychometrika, 47, 41–54.

    Article  Google Scholar 

  • Jennrich, R.I. (2001). A simple general procedure for orthogonal rotation. Psychometrika, 66, 289–306.

    Article  Google Scholar 

  • Patrick, C.J., Hicks, B.M., Nichol, P.E., & Krueger, R.F. (2007). A bi-factor approach to modeling the structure of the Psychopathy checklist-revisited. Journal of Personality Disorders, 21, 118–141.

    Article  PubMed  Google Scholar 

  • Pomplun, M. (2007). A bifactor analysis for a mode-of-administration effect. Applied Measurement in Education, 20, 137–152.

    Article  Google Scholar 

  • Reise, S.P., Morizot, J., & Hays, R.D. (2007). The role of the bifactor model in resolving dimensionality issues in health outcomes measures. Medical Care, 16, 19–31.

    Google Scholar 

  • Reise, S.P., Moore, T.M., & Haviland, M.G. (2010). Bi-factor models and rotations: Exploring the extent to which multidimensional data yield univocal scale scores. Journal of Personality Assessment, 92, 544–559.

    Article  PubMed  Google Scholar 

  • Schmid, J., & Leiman, J.M. (1957). The development of hierarchical factor solutions. Psychometrika, 22, 53–61.

    Article  Google Scholar 

  • Simms, L.J., Grös, D.F., Watson, D., & O’Hara, M.W. (2008). Parsing the general and specific components of depression and anxiety with bifactor modeling. Depression and Anxiety, 25, E34–E46.

    Article  PubMed  Google Scholar 

  • Yung, Y.-F., Thissen, D., & McLeod, L.D. (1999). On the relation between the higher-order factor model and the hierarchical factor model. Psychometrika, 64, 113–128.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Robert I. Jennrich.

Additional information

An erratum to this article is available at http://dx.doi.org/10.1007/s11336-013-9346-0.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jennrich, R.I., Bentler, P.M. Exploratory Bi-Factor Analysis. Psychometrika 76, 537–549 (2011). https://doi.org/10.1007/s11336-011-9218-4

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11336-011-9218-4

Keywords

Navigation