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(Version, updated on 2023-08-30, release history)

semfindr: Finding influential cases in SEM

A find(e)r of influential cases in structural equation modeling based mainly on the sensitivity analysis procedures presented by Pek and MacCallum (2011).

This package supports two approaches: leave-one-out analysis and approximate case influence.

Leave-One-Out Analysis

This approach examines the influence of each case by refitting a model with this case removed.

Unlike other similar packages, the workflow adopted in semfindr separates the leave-one-out analysis (refitting a model with one case removed) from the case influence measures.

This approaches avoids unnecessarily refitting the models for each set of influence measures, and also allows analyzing only probable influential cases when the model takes a long time to fit.

The functions were designed to be flexible such that users can compute case influence measures such as

This package can also be generate plots to visualize case influence, including a bubble plot similar to that by car::influencePlot() All plots generated are ggplot plots that can be further modified by users. More can be found in Quick Start (vignette("semfindr", package = "semfindr")).

Approximate Case Influence

This approach computes the approximate influence of each case using casewise scores and casewise likelihood. This method is efficient because it does not requires refitting the model for each case. However, it can only approximate the influence, unlike the leave-one-out approach, which produce exact influence. This approach can be used when the number of cases is very large and/or the model takes a long time to fit. Technical details can be found in the vignette Approximate Case Influence Using Scores and Casewise Likelihood (vignette("casewise_scores", package = "semfindr")).


The latest developmental version can be installed by remotes::install_github:


You can learn more about this package at the Github page of this package and Quick Start (vignette("semfindr", package = "semfindr")).


Pek, J., & MacCallum, R. (2011). Sensitivity analysis in structural equation models: Cases and their influence. Multivariate Behavioral Research, 46(2), 202-228.

Comments, Suggestions, and Bug Reports

Please post your comments, suggestions, and bug reports as issues at GitHub, or contact the maintainer by email. Thanks in advance for trying out semfindr.