Dr. Walter Leite Provides Tutorial on Sensitivity Analysis Methods

Dr. Walter Leite will provide a tutorial on sensitivity analysis methods for structural equation modeling at the Modern Modeling Methods Conference, June 26-28, University of Connecticut.

A Tutorial on Methods for Sensitivity Analysis to Omitted Confounders in Structural Equation Modeling

A few sensitivity analysis methods for structural equation modeling (SEM) have been developed recently based on using phantom variables to represent a potential omitted confounder. Sensitivity analysis is an important tool to probe the boundaries of the conclusions of a research study. However, these methods have not been widely disseminated in the SEM user community. We will provide a tutorial of methods for sensitivity analysis in SEM implemented in the SEMsens package of the R Statistical Software.  The sensitivity analysis shown in the tutorial is for a complex SEM of the relationship between job satisfaction and turnover. The results of the sensitivity analysis show how conclusions about explanatory theories may be susceptible to unobserved relationships with omitted confounders.