semfindr: An R Package for Identifying Influential Cases in Structural Equation Modeling

Measuring case influence on parameter estimates and model fit measures, which is one type of sensitivity analysis, is important for assessing the robustness of findings in structural equation modeling (SEM). However, it was rarely reported clearly or was conducted inappropriately, mistaking outlier detection for influential cases assessment. Some existing tools have limitations in the models or estimation methods they support, or in the types of influence measures that can be computed. We developed an easy-to-use R package, semfindr, for identifying influential cases in SEM using the leave-one-out (LOO) method. It reduces the computational cost by separating the refitting step from the case influence computation step. It also has various plot functions for effective assessment of case influence in complicated models. Lastly, it supports multiple-group models and the handling of missing data. This manuscript demonstrates how to utilize semfindr for efficient search for influential cases, providing publication-ready results and plots.