Model Specification Searches in Structural Equation Modeling with a Hybrid Ant Colony Optimization Algorithm. Issue 5 (3rd September 2022)

• Record Type: Journal Article
• Authors: Jing, Zeyuan; Kuang, Huan; Leite, Walter L.; Marcoulides, Katerina M.; Fisk, Charles L.
• Is Part Of: Structural equation modeling. Volume 29:Issue 5(2022)
• Page Start: 655
• Page End: 666
• Publication Date: 2022-09-03
• Subjects: Ant Colony Optimization algorithm -- data mining -- metaheuristic algorithm -- model misspecification -- specification search -- structural equation modeling -- Tabu Search; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2021.2020119
• Languages: English
• ISSNs: 1070-5511

Abstract

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.