Category Skew and Discriminant Validity With Likert-Type Items: Code and Results

Code and results accompanying: Zhang, J. (2026). Category skew can make identical constructs look distinct: Discriminant validity assessment with Likert-type items [Manuscript submitted for publication]. The archives contain the Python code for the exact population computations (Study 1); the R/lavaan code for the Monte Carlo simulation, with all seeds (Study 2; 174 conditions, 1,000 replications each); the code for the real-data check with the SAPA Personality Inventory (Study 3); the R function skew_htmt_check() printed in Appendix B; all condition-level results; the per-replication estimates of Study 2; and the figures. README.md maps each table and figure in the article to the file that produces it. Version 1.0.1 redraws Figures 1 and 2 (the in-panel label of Figure 1 and the y-axis ranges of both figures only; no data or results changed) and splits the material into three archives: Paper4_code_and_results.zip, Paper4_study2_replications_core.zip, and Paper4_study2_replications_ext.zip. Unzip all three into the same folder.