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Updated: Feb 5, 2026

A Rapid Method for Modeling a Variable Cycle Engine
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Model Implied Instrumental Variables (MIIVs): An Alternative Orientation to Structural Equation Modeling.

Kenneth A Bollen1

  • 1a Departments of Psychology and Neuroscience and Sociology , University of North Carolina , Chapel Hill , NC , USA.

Multivariate Behavioral Research
|September 18, 2018
PubMed
Summary

The Model Implied Instrumental Variable (MIIV) approach offers a robust alternative to traditional structural equation modeling (SEM) estimators. MIIV-2SLS provides better misspecification detection and flexibility for complex models.

Keywords:
Local testsmodel implied instrumental variablesrobust estimatorstructural equation modelingstructural misspecifications

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Area of Science:

  • Statistics
  • Econometrics
  • Psychometrics

Background:

  • Traditional structural equation modeling (SEM) estimators often assume model correctness.
  • Maximum likelihood estimators can produce biased results when models are misspecified.
  • Alternative methods are needed for robust SEM analysis.

Purpose of the Study:

  • To provide an overview of the Model Implied Instrumental Variable (MIIV) approach for SEM.
  • To highlight the advantages of the MIIV estimator using Two Stage Least Squares (MIIV-2SLS).
  • To demonstrate the applicability of MIIV methods across various statistical models.

Main Methods:

  • Overview of the Model Implied Instrumental Variable (MIIV) approach.
  • Application of Two Stage Least Squares (2SLS) for MIIV estimation (MIIV-2SLS).
  • Discussion of equation-based overidentification tests for misspecification detection.

Main Results:

  • MIIV-2SLS exhibits greater robustness to structural misspecifications compared to system-wide estimators.
  • The MIIV-2SLS estimator is asymptotically distribution-free.
  • MIIV-2SLS facilitates the identification of model misspecifications through overidentification tests.

Conclusions:

  • The MIIV approach offers a flexible and robust alternative for SEM, applicable to diverse models.
  • MIIV-2SLS allows for focused estimation and testing of specific model subsets.
  • Further research is recommended to explore MIIV-2SLS performance in empirical settings.