Improved Accuracy: By accounting for heteroscedasticity, WLS provides more reliable estimates of regression coefficients, which is crucial for risk assessment and determining safe exposure limits. Better Model Fit: WLS can yield a better fit for data by aligning the model more closely with the underlying data distribution, which is essential for accurately characterizing the toxicological profiles of substances. Flexibility in Analysis: WLS is adaptable to various types of data distributions and can be tailored to handle complex datasets typical in toxicological research.
