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Selection of variables in exploratory factor analysis: An empirical comparison of a stepwise and traditional approach

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  • Kristine Hogarty

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  • Jeffrey Kromrey
  • John Ferron
  • Constance Hines

Abstract

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Suggested Citation

  • Kristine Hogarty & Jeffrey Kromrey & John Ferron & Constance Hines, 2004. "Selection of variables in exploratory factor analysis: An empirical comparison of a stepwise and traditional approach," Psychometrika, Springer;The Psychometric Society, vol. 69(4), pages 593-611, December.
  • Handle: RePEc:spr:psycho:v:69:y:2004:i:4:p:593-611
    DOI: 10.1007/BF02289857
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    References listed on IDEAS

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    1. Yutaka Kano & Akira Harada, 2000. "Stepwise variable selection in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 65(1), pages 7-22, March.
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    Cited by:

    1. Brusco, Michael J. & Steinley, Douglas, 2011. "Exact and approximate algorithms for variable selection in linear discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 123-131, January.
    2. Tangian, Andranik S., 2017. "Selection of questions for VAAs and the VAA-based elections," Working Paper Series in Economics 100, Karlsruhe Institute of Technology (KIT), Department of Economics and Business Engineering.
    3. Michael Brusco & Renu Singh & Douglas Steinley, 2009. "Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 705-726, December.
    4. Pacheco, JoaquĆ­n & Casado, Silvia & Porras, Santiago, 2013. "Exact methods for variable selection in principal component analysis: Guide functions and pre-selection," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 95-111.
    5. Brusco, Michael J., 2014. "A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 38-53.

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