Title: Using Simulated Annealing to Investigate Sensitivity of SEM to External Model Misspecification.
Authors: Fisk, Charles L.; Harring, Jeffrey R.; Shen, Zuchao; Leite, Walter; Suen, King Yiu; Marcoulides, Katerina M.
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.
Subjects: STRUCTURAL equation modeling; RESEARCH; SELF-perception; INTELLECT; SENSITIVITY & specificity (Statistics); EMPIRICAL research; ALGORITHMS; EVALUATION
Publication: Educational & Psychological Measurement, 2023, Vol 83, Issue 1, p73
ISSN: 0013-1644
Publication type: Academic Journal
DOI: 10.1177/00131644211073121

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

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