Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic

  • Theory and Methods
  • Published:
Psychometrika Aims and scope Submit manuscript

Abstract

A scaled difference test statistic \(\tilde{T}{}_{d}\) that can be computed from standard software of structural equation models (SEM) by hand calculations was proposed in Satorra and Bentler (Psychometrika 66:507–514, 2001). The statistic \(\tilde{T}_{d}\) is asymptotically equivalent to the scaled difference test statistic \(\bar{T}_{d}\) introduced in Satorra (Innovations in Multivariate Statistical Analysis: A Festschrift for Heinz Neudecker, pp. 233–247, 2000), which requires more involved computations beyond standard output of SEM software. The test statistic \(\tilde{T}_{d}\) has been widely used in practice, but in some applications it is negative due to negativity of its associated scaling correction. Using the implicit function theorem, this note develops an improved scaling correction leading to a new scaled difference statistic \(\bar{T}_{d}\) that avoids negative chi-square values.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Bentler, P.M. (2008). EQS 6 structural equations program manual. Encino: Multivariate Software.

    Google Scholar 

  • Bentler, P.M., Satorra, A., & Yuan, K.-H. (2009). Smoking and cancers: case-robust analysis of a classic data set. Structural Equation Modeling, 16, 382–390.

    Article  PubMed  Google Scholar 

  • Bollen, K.A., & Curran, P.J. (2006). Latent curve models: a structural equation perspective. New York: Wiley.

    Google Scholar 

  • Bonett, D.G., Woodward, J.A., & Randall, R.L. (2002). Estimating p-values for Mardia’s coefficients of multivariate skewness and kurtosis. Computational Statistics, 17, 117–122.

    Article  Google Scholar 

  • Browne, M.W. (1984). Asymptotically distribution-free methods for the analysis of covariance structures. British Journal of Mathematical and Statistical Psychology, 37, 62–83.

    PubMed  Google Scholar 

  • Grace, J.B. (2006). Structural equation modeling and natural systems. New York: Cambridge University Press.

    Book  Google Scholar 

  • Satorra, A. (1989). Alternative test criteria in covariance structure analysis: a unified approach. Psychometrika, 54, 131–151.

    Article  Google Scholar 

  • Satorra, A. (2000). Scaled and adjusted restricted tests in multi-sample analysis of moment structures. In D.D.H. Heijmans & D.S.G. Pollock, A. Satorra (Eds.), Innovations in multivariate statistical analysis: a festschrift for Heinz Neudecker (pp. 233–247). Dordrecht: Kluwer Academic.

    Google Scholar 

  • Satorra, A., & Bentler, P.M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C.C. Clogg (Eds.) Latent variables analysis: applications for developmental research (pp. 399–419). Thousand Oaks: Sage.

    Google Scholar 

  • Satorra, A., & Bentler, P.M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66, 507–514.

    Article  Google Scholar 

  • Satorra, A., & Bentler, P.M. (2008). Ensuring positiveness of the scaled difference chi-square test statistic. Department of Statistics, UCLA Department of Statistics Preprint. http://repositories.cdlib.org/uclastat/papers/2008010905.

  • Yuan, K.-H., & Bentler, P.M. (2007). Structural equation modeling. In C.R. Rao & S. Sinharay (Eds.) Handbook of statistics 26: Psychometrics (pp. 297–358). Amsterdam: North-Holland.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Albert Satorra.

Additional information

Research supported by grants SEJ2006-13537 and PR2007-0221 from the Spanish Ministry of Science and Technology and by USPHS grants DA00017 and DA01070.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Satorra, A., Bentler, P.M. Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic. Psychometrika 75, 243–248 (2010). https://doi.org/10.1007/s11336-009-9135-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11336-009-9135-y

Keywords

Navigation