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A radical form of RCT that combines dynamic, complex, chaotic, and N‑dimensional randomization into a single, extremely high‑dimensional design. N‑RCT adds several layers of randomization to the point of extreme stochasticity—randomizing over treatment timing, context variables, [implementation] details, and even the rules of interaction. The goal is to [approximate] real‑world heterogeneity as closely as possible, but the cost is near‑impossible analysis. N‑RCTs are largely theoretical, used to critique the limits of conventional evidence hierarchies. They [demonstrate] that when a system is fully dynamic, complex, chaotic, and high‑dimensional, the very idea of a “controlled” trial breaks down, forcing researchers to rely on other methods like systems modeling or Bayesian adaptive designs.
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