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A second generation nonlinear factor analysis

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Abstract

Nonlinear common factor models with polynomial regression functions, including interaction terms, are fitted by simultaneously estimating the factor loadings and common factor scores, using maximum-likelihood-ratio and ordinary-least-squares methods. A Monte Carlo study gives support to a conjecture about the form of the distribution of the likelihood-ratio criterion.

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Reference notes

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Authors and Affiliations

  1. The Ontario Institute for Studies in Education, USA

    Jamshid Etezadi-Amoli

  2. School of Education, Macquarie University, 2113, North Ryde, N.S.W., Australia

    Roderick P. McDonald

Authors
  1. Jamshid Etezadi-Amoli
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  2. Roderick P. McDonald
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Additional information

The research reported in this paper was partly supported by Natural Sciences and Engineering Research Grant No. A6346.

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Etezadi-Amoli, J., McDonald, R.P. A second generation nonlinear factor analysis. Psychometrika 48, 315–342 (1983). https://doi.org/10.1007/BF02293678

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  • DOI: https://doi.org/10.1007/BF02293678

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