Identification of Suicide-Related Subgroups Using Latent Class Analysis: Complementary Insights to Explainable AI–Based Classification
This repository contains the code and materials used for the study:
Objective: To identify latent subgroups of individuals based on suicide-related characteristics using latent class analysis (LCA) and to compare these subgroups with feature importance patterns derived from explainable artificial intelligence (XAI) methods, including SHAP values (Tang et al., 2024).
This study uses the same publicly available dataset as in the XAI paper (Tang et al., 2024)., making the analyses fully reproducible with open-access code and data.
git clone https://github.com/busenurk/suicide-lca-comparison.gitThis repository is released under the MIT License. See the LICENSE file for details.
If you use this work in your research, a citation would be much appreciated — the scholarly version of a thank-you note. 🌷