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Efficient estimation and local identification in latent class analysis

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Abstract

Estimators which are efficient in the sense of having minimum asymptotic variance are obtained for the structural parameters of Lazarsfeld's latent class model of latent structure analysis. Sufficient conditions for the local identification of the structural parameters are also presented.

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References

  1. Anderson, T. W. On estimation of parameters in latent structure analysis.Psychometrika, 1954,19, 1–10.

    Article  Google Scholar 

  2. Coombs, C. H. A theory of psychological scaling. Eng. Res. Bull. No. 34, University of Michigan, 1952.

  3. Fisher, R. A. The conditions under which chi square measures the discrepancy between observation and hypothesis.J. R. stat. Soc., 1924,87, 442–450.

    Google Scholar 

  4. Gulliksen, H. Theory of mental tests. New York; Wiley, 1950.

    Google Scholar 

  5. Hurwicz, L. Generalization of the concept of identification. Statistical inference in dynamic economic models. Cowles Commission Monograph 10. 1950, 245–257.

  6. Koopmans, T. C. and Reiersøl, O. The identification of structural characteristics.Ann. math. Stat., 1950,21, 165–181.

    Google Scholar 

  7. Lord, F. A theory of test scores. Psychometric Monograph, No. 7, 1952.

  8. Neyman, J. Contribution to the theory of the x2-test. Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability. Berkeley: University California Press, 1949.

    Google Scholar 

  9. Neyman, J. and Scott, E. L. Consistent estimates based on partially consistent observations.Econometrica, 1948,16, 1–32.

    Google Scholar 

  10. Rao, C. R. Advanced statistical methods in biometric research. New York: Wiley, 1952.

    Google Scholar 

  11. Reiersøl, O. On the identifiability of parameters in Thurstone's multiple-factor analysis.Psychometrika, 1950,15, 121–149.

    Article  PubMed  Google Scholar 

  12. Schumacher, C. F., Maxson, G. R., and Martinek, H. Tests for creative ability in machine design. Annual report, 1953. Project ONR 458. Armed Services Technical Information Agency 21 284.

  13. Stevens, S. S. Handbook of experimental psychology. New York: Wiley, 1951.

    Google Scholar 

  14. Stouffer, S. A., Lazarsfeld, P. F., et al. Measurement and prediction. Princeton: Princeton Univ. Press, 1950.

    Google Scholar 

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Authors and Affiliations

  1. Iowa State College, USA

    Richard B. McHugh

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  1. Richard B. McHugh
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Additional information

The writer wishes to acknowledge with appreciation the helpful advice of Professors Leonid Hurwicz and Jacob Bearman of the University of Minnesota. Dr. John Gurland of Iowa State College assisted the author in clarifying certain points in this article.

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McHugh, R.B. Efficient estimation and local identification in latent class analysis. Psychometrika 21, 331–347 (1956). https://doi.org/10.1007/BF02296300

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  • DOI: https://doi.org/10.1007/BF02296300

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