Python Script for Simulating, Analyzing, and Evaluating Qualitative Exposuremetrics Estimators

This document presents a comprehensive validation study of the Qualitative Exposuremetrics estimators—novel tools designed for analyzing organismal resistance and susceptibility dynamics using qualitative variables. The validation was conducted using datasets derived from Monte Carlo simulation experiments and real-world case scenarios. The study assesses and compares the statistical robustness, efficiency, and behavior of the qualitative exposuremetrics estimators against classical methods commonly used in exposure-response data analysis. By providing both simulated and empirical datasets, this work enhances transparency, reproducibility, and practical understanding of the estimators, thereby supporting wider adoption and usability in relevant research contexts.