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On the interpretation of factor analysis

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  • Armstrong, J. Scott
  • Soelberg, Peer

Abstract

The importance of the researcher’s interpretation of factor analysis is illustrated by means of an example. The results from this example appear to be meaningful and easily interpreted. The example omits any measure of reliability or validity. If a measure of reliability had been included, it would have indicated the worthlessness of the results. A survey of 46 recent papers from 6 journals supported the claim that the example is typical, two thirds of the papers provide no measure of reliability. In fact, some papers did not even provide sufficient information to allow for replication. To improve the current situation some measure of factor reliability should accompany applied studies that utilize factor analysis. Three operational approaches are suggested for obtaining measures of factor reliability: use of split samples, Monte Carlo simulation, and a priori models.

Suggested Citation

  • Armstrong, J. Scott & Soelberg, Peer, 1968. "On the interpretation of factor analysis," MPRA Paper 81665, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:81665
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    References listed on IDEAS

    as
    1. J. Guilford, 1961. "Psychological measurement a hundred and twenty-five years later," Psychometrika, Springer;The Psychometric Society, vol. 26(1), pages 109-127, March.
    2. Louis Guttman, 1954. "Some necessary conditions for common-factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 19(2), pages 149-161, June.
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    Cited by:

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    2. Ilse Botha, 2010. "A Comparative Analysis Of The Synchronisation Of Business Cycles For Developed And Developing Economies With The World Business Cycle," South African Journal of Economics, Economic Society of South Africa, vol. 78(2), pages 192-207, June.
    3. Maurizio Vichi, 2017. "Disjoint factor analysis with cross-loadings," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(3), pages 563-591, September.
    4. Freeman, Steven F. & International Motor Vehicle Program., 1993. "Identity maintenance and adaptation : multilevel analysis of response to loss," Working papers w-0093a, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    5. Amare Abawa Esubalew & A. Raghurama, 2021. "The moderating effect of size on the relationship between commercial banks financing and the performance of micro, small, and medium enterprises (MSMEs)," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 11(1), pages 1-14, December.
    6. Carlos M. Del Rio & Lyle J. White, 2014. "Hylomorphic Attitudinal Spirituality," SAGE Open, , vol. 4(1), pages 21582440135, January.
    7. Brosnan, Kylie & Grün, Bettina & Dolnicar, Sara, 2018. "Identifying superfluous survey items," Journal of Retailing and Consumer Services, Elsevier, vol. 43(C), pages 39-45.
    8. Yang Zhang & Su Zhang & Fu-Chieh Hsu, 2023. "Crisis Management Performance of Upscale Hotels in the Greater Bay Area, China: A Comparative Study in a Complex Institutional Situation," Sustainability, MDPI, vol. 15(6), pages 1-24, March.

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    More about this item

    Keywords

    factor analysis; statistics; marketing;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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