Using Ant Colony Optimization for Sensitivity Analysis in Structural Equation Modeling

• In Event: Sensitivity Analysis in Structural Equation Modeling

Abstract

The results of structural equation modeling (SEM) may be vital to the development of theory of action and potentially serve as the key knowledge base for decision making. Meanwhile, any SEM analysis may suffer from the impact of a potential missing confounder that may change its conclusions (Harring, McNeish, & Hancock, 2017). The purpose of this study is to develop a tool to evaluate the sensitivity of structural equation models to potential missing confounders using the Ant Colony Optimization (ACO; Colorni, Dorigo, & Maniezzo, 1992; Dorigo & Stützle, 2004; Socha & Dorigo, 2008) algorithm.

Authors

• Zuchao Shen, University of Georgia

• Walter L. Leite, University of Florida