C-Test Collector: A Proficiency Testing Application to Collect Training Data for C-Tests. - Christian Haring; René Lehmann; Andrea Horbach; Torsten Zesch (BEA@EACL, 2021)

Increasing the Power of Two-Sample T-tests in Health Psychology Using a Compositional Data Approach. - René Lehmann; Bodo Vogt (BI, 2023)

Reconsidering Bipolar Scales Data As Compositional Data Improves Psychometric Healthcare Data Analytics. - René Lehmann; Bodo Vogt (HICSS, 2023)

Empirical Insights into the Value of a Novel Compositional Data Approach for Analyzing Bipolar Likert Scale Data. - René Lehmann; Bodo Vogt (BI (1), 2024)

Increasing normal approximation in psychometric health care data analyses using a compositional data approach. - René Lehmann; Bodo Vogt (HICSS, 2024)

Compositional data statistics improves smart tourism data analytics: profound managerial decisions through reduced statistical bias and increased power. - René Lehmann; Bodo Vogt (HICSS, 2024)

Shifting psychometric bipolar scales data towards the normal distribution. - René Lehmann; Bodo Vogt (HICSS, 2024)

Towards Interoperability of APIs - an LLM-based approach. - René Lehmann (Middleware Demos/Posters/Doctoral Symposium, 2024)

Robustness of the Compositional Data Approach in Bipolar Psychometric Likert Scales Big Skewed Data Analysis. - René Lehmann; Bodo Vogt (WI/IAT, 2024)

Improving Likert scale big data analysis in psychometric health economics: reliability of the new compositional data approach. - René Lehmann; Bodo Vogt (Brain Informatics, 2024)

Navigating the Security Challenges of LLMs: Positioning Target-Side Defenses and Identifying Research Gaps. - Malte Josten; Matthias Schaffeld; René Lehmann; Torben Weis (ICISSP (2), 2025)

Breakdown of the compositional data approach in psychometric Likert scale big data analysis: about the loss of statistical power of two-sample t-tests applied to heavy-tailed big data. - René Lehmann; Bodo Vogt (Brain Informatics, 2025)