RA/Chaos-Theory Series — Paper 13 Evidence at the Edge: Statistical Interpretation in Transition-Prone Inflammatory Disease

This paper examines the methodological implications of The Law of the Edge (Paper 12) for clinical research in chronic inflammatory disease. If health represents bounded instability within a coherent adaptive system, and disease reflects attractor consolidation beyond adaptive variance, then early transition phases may not manifest primarily as shifts in mean disease activity. Conventional randomized controlled trials are optimized to detect differences in central tendency. However, transition-prone inflammatory systems may initially exhibit altered stability structure—such as increased variance, rising temporal autocorrelation, or slowed recovery dynamics—before overt mean displacement occurs. Under such conditions, statistical non-significance does not necessarily indicate absence of biological effect but may reflect insufficient dynamical resolution or aggregation across heterogeneous stability states. This manuscript argues for cautious interpretation of non-significant findings in nonlinear disease systems and outlines methodological considerations for integrating stability-sensitive metrics into clinical research design. This work forms part of the RA/Chaos-Theory Series (Papers 1–13), documenting the stepwise development of a dynamical systems framework for chronic inflammatory disease. This manuscript is released as a preprint and has not undergone peer review.