Sensitivity analysis for structural equation modeling (SEM)

Dr. Walter Leite describes sensitivity analysis to omitted confounders for structural equation modeling. This video is based on the following papers:

Harring, J. R., McNeish, D. M., & Hancock, G. R. (2017). Using phantom variables in structural equation modeling to assess model sensitivity to external misspecification. Psychological Methods, 22(4), 616-631. https://doi.org/10.1037/met0000103

Leite, W. L., Shen, Z., Marcoulides, K., Fisk, C. L., & Harring, J. (2021). Using Ant Colony Optimization for Sensitivity Analysis in Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal, 1-10. https://doi.org/10.1080/10705511.2021.1881786

More information can be found here:
https://cran.r-project.org/web/packages/SEMsens/index.html
https://osf.io/f6mgj/