Using Simulated Annealing to Investigate Sensitivity of SEM to External Model Misspecification

Charles L Fisk; Jeffrey R Harring; Zuchao Shen; Walter Leite; King Yiu Suen; Katerina M Marcoulides

doi:10.1177/00131644211073121

Using Simulated Annealing to Investigate Sensitivity of SEM to External Model Misspecification

Educ Psychol Meas. 2023 Feb;83(1):73-92. doi: 10.1177/00131644211073121. Epub 2022 Jan 31.

Authors

Charles L Fisk¹, Jeffrey R Harring¹, Zuchao Shen², Walter Leite², King Yiu Suen³, Katerina M Marcoulides³

Affiliations

¹ University of Maryland, College Park, USA.
² University of Florida, Gainesville, USA.
³ University of Minnesota, Minneapolis, USA.

Abstract

Sensitivity analyses encompass a broad set of post-analytic techniques that are characterized as measuring the potential impact of any factor that has an effect on some output variables of a model. This research focuses on the utility of the simulated annealing algorithm to automatically identify path configurations and parameter values of omitted confounders in structural equation modeling (SEM). An empirical example based on a past published study is used to illustrate how strongly related an omitted variable must be to model variables for the conclusions of an analysis to change. The algorithm is outlined in detail and the results stemming from the sensitivity analysis are discussed.

Keywords: metaheuristic algorithms; optimization; sensitivity analysis; simulated annealing; structural equation modeling.