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The analysis of structural equation models by means of derivative free nonlinear least squares

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  • Sik-Yum Lee
  • Robert Jennrich

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  • Sik-Yum Lee & Robert Jennrich, 1984. "The analysis of structural equation models by means of derivative free nonlinear least squares," Psychometrika, Springer;The Psychometric Society, vol. 49(4), pages 521-528, December.
    • Handle: RePEc:spr:psycho:v:49:y:1984:i:4:p:521-528
    DOI: 10.1007/BF02302589
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    References listed on IDEAS

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    1. Sik-Yum Lee, 1980. "Estimation of covariance structure models with parameters subject to functional restraints," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 309-324, September.
    2. S. Lee & R. Jennrich, 1979. "A study of algorithms for covariance structure analysis with specific comparisons using factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 44(1), pages 99-113, March.
    3. Karl Jöreskog & Arthur Goldberger, 1972. "Factor analysis by generalized least squares," Psychometrika, Springer;The Psychometric Society, vol. 37(3), pages 243-260, September.
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    Citations

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    Cited by:

    1. Bagozzi, Richard P. & Yi, Youjae & Nassen, Kent D., 1998. "Representation of measurement error in marketing variables: Review of approaches and extension to three-facet designs," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 393-421, November.
    2. Robert Cudeck & Kelli Klebe & Susan Henly, 1993. "A simple Gauss-Newton procedure for covariance structure analysis with high-level computer languages," Psychometrika, Springer;The Psychometric Society, vol. 58(2), pages 211-232, June.
    3. Robert Cudeck, 1986. "A note on structural models for the circumplex," Psychometrika, Springer;The Psychometric Society, vol. 51(1), pages 143-147, March.

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