Model Specification Searches in Structural Equation Modeling with a Hybrid Ant Colony Optimization Algorithm

Zeyuan Jing, Huan Kuang, Walter L. Leite, Katerina M. Marcoulides, Charles L. Fisk

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Model specification is a crucial aspect of structural equation modeling (SEM), since a misspecified model may lead to biased parameter estimation and result in inaccurate conclusions. We propose the Hybrid Ant Colony Optimization Algorithm (hACO), an improved metaheuristic algorithm to conduct model specification searches in SEM. This data mining algorithm combines aspects of the Ant Colony Optimization algorithm with the Tabu search algorithm to increase both accuracy and efficiency. A Monte Carlo simulation study showed that the hACO algorithm provided accurate and efficient SEM specification searches across all designed simulation conditions. The hACO algorithm can help applied researchers conduct specification searches while avoiding potential model misspecifications.

Original languageEnglish (US)
Pages (from-to)655-666
Number of pages12
JournalStructural Equation Modeling
Volume29
Issue number5
DOIs
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 Taylor & Francis Group, LLC.

Keywords

  • Ant Colony Optimization algorithm
  • Tabu Search
  • data mining
  • metaheuristic algorithm
  • model misspecification
  • specification search
  • structural equation modeling

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