A non-iterative approach to estimating parameters in a linear structural equation model

Li Ping Zhu, Lixing ZHU*, Shi Song Mao

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

1 Citation (Scopus)


The research described herein was motivated by a study of the relationship between the performance of students in senior high schools and at universities in China. A special linear structural equation model is established, in which some parameters are known and both the responses and the covariables are measured with errors. To explore the relationship between the true responses and latent covariables and to estimate the parameters, we suggest a non-iterative estimation approach that can account for the external dependence between the true responses and latent covariables. This approach can also deal with the collinearity problem because the use of dimension-reduction techniques can remove redundant variables. Combining further with the information that some of parameters are given, we can perform estimation for the other unknown parameters. An easily implemented algorithm is provided. A simulation is carried out to provide evidence of the performance of the approach and to compare it with existing methods. The approach is applied to the education example for illustration, and it can be readily extended to more general models.

Original languageEnglish
Pages (from-to)65-78
Number of pages14
JournalJournal of Applied Statistics
Issue number1
Publication statusPublished - Jan 2006

Scopus Subject Areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • Canonical correlation analysis
  • Collinearity
  • Linear structural equation model
  • Partial least squares


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