Comparison of Conventional and Neutrosophic Methods for Statistical Power Analysis and Effect Size in Clinical Research

The study investigates the integration of conventional statistical methods with neutrosophic techniques for effect size and statistical power analysis in clinical research. It addresses a significant gap in applying neutrosophic methodologies to complex datasets characterized by uncertainty and variability. Conventional methods, such as Cohen’s d, assume well-defined data, which limits their effectiveness in real-world clinical scenarios. Neutrosophic methods incorporate degrees of truth, falsity, and indeterminacy and are more suitable for analyzing uncertain and inconsistent clinical data. For instance, when comparing blood pressure reduction between a Treatment Group and a Control Group, conventional methods yield an effect size of 3.00 and a power of 99%. In contrast, neutrosophic methods result in an effect size of 13.46 and a power of 100%, highlighting their ability to manage data complexities better. The findings emphasize the need to integrate neutrosophic techniques into clinical analysis to improve effect size and power estimation accuracy and reliability, especially in studies with variable data. However, the study is limited to a specific dataset, and further research is needed across different clinical domains. Neutrosophic methods might also require advanced resources and expertise, which could be challenging in some settings. This study presents a novel approach that improves our understanding of clinical outcomes.