Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A two-stage estimation of structural equation models with continuous and polytomous variables

S Y Lee1, W Y Poon, P M Bentler

  • 1Department of Statistics, Chinese University of Hong Kong, Shatin, NT, Hong Kong.

The British Journal of Mathematical and Statistical Psychology
|November 1, 1995
PubMed
Summary

This study introduces an efficient computational method for analyzing structural equation models with mixed variable types. The new procedure enhances accuracy and robustness for complex statistical modeling.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Invariant Standardized Estimated Parameter Change for Model Modification in Covariance Structure Analysis.

Multivariate behavioral research·2016
Same author

A NEW MATRIX FOR THE ASSESSMENT OF FACTOR CONTRIBUTIONS.

Multivariate behavioral research·2016
Same author

Brief Report: An Additional Minimal Transformation To Orthonormality.

Multivariate behavioral research·2016
Same author

The Relationship Of Personality Structure To Patterns Of Adolescent Substance Use.

Multivariate behavioral research·2016
Same author

Interrelations Among Models For The Analysis Of Moment Structures.

Multivariate behavioral research·2016
Same author

Longitudinal Analysis Of The Role Of Peer Support, Adult Models, And Peer Subcultures In Beginning Adolescent Substance Use: An Application Of Setwise Canonical Correlation Methods.

Multivariate behavioral research·2016

Area of Science:

  • Statistics
  • Quantitative Psychology
  • Econometrics

Background:

  • Structural Equation Models (SEM) are widely used but analyzing models with mixed continuous and polytomous variables presents computational challenges.
  • Existing methods may lack efficiency or robustness when dealing with heterogeneous data types within SEM.

Purpose of the Study:

  • To develop a computationally efficient procedure for the analysis of structural equation models (SEM) involving both continuous and polytomous variables.
  • To provide a robust estimation method for parameters in mixed-variable SEM.

Main Methods:

  • A two-stage approach combining partition maximum likelihood (PML) for initial estimates and generalized least squares (GLS) for structural parameter estimation.
  • Utilizes estimates of thresholds, polyserial, and polychoric correlations within an asymptotic distribution framework.

Related Experiment Videos

Main Results:

  • The proposed procedure demonstrates computational efficiency for mixed-variable SEM.
  • Asymptotic properties of the derived estimators are established, providing theoretical guarantees.
  • Simulation studies indicate favorable empirical performance and robustness compared to existing methods.

Conclusions:

  • The developed method offers an efficient and robust solution for analyzing structural equation models with continuous and polytomous variables.
  • This approach advances the practical application of SEM in fields dealing with mixed data types.