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A comparison of several approximations to the power function of the likelihood ratio test in covariance structure analysis

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  • A. Satorra
  • W.E. Saris
  • W.M. de Pijper

Abstract

In this paper we compare alternative asymptotic approximations to the power of the likelihood ratio test used in covariance structure analysis for testing the fit of a model. Alternative expressions for the noncentrality parameter (ncp) lead to different approximations to the power function. It appears that for alternative covariance matrices close to the null hypothesis, the alternative ncp's lead to similar values, while for alternative covariance matrices far from Ho the different expressions for the ncp can conflict substantively. Monte Carlo evidence shows that the ncp proposed in Satorra and Saris (1985) gives the most accurate power approximations.

Suggested Citation

  • A. Satorra & W.E. Saris & W.M. de Pijper, 1991. "A comparison of several approximations to the power function of the likelihood ratio test in covariance structure analysis," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 45(2), pages 173-185, June.
    • Handle: RePEc:bla:stanee:v:45:y:1991:i:2:p:173-185
    DOI: 10.1111/j.1467-9574.1991.tb01302.x
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    Cited by:

    1. Ke-Hai Yuan & Wai Chan, 2005. "On Nonequivalence of Several Procedures of Structural Equation Modeling," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 791-798, December.
    2. Steven Glazerman & John Mullens & Angie KewalRamani & David Myers, "undated". "Strategies for Measuring the Impacts of Federal Reading Programs on Reading Achievement," Mathematica Policy Research Reports 67b276b63f834876b09664647, Mathematica Policy Research.
    3. Albert Satorra, 2015. "A Comment on a Paper by H. Wu and M. W. Browne (2014)," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 613-618, September.

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