T-Optimality for Model Discrimination in Non-Nested Models (medical studies)
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Abstract
T-optimality is a design criterion in model discrimination, aiming to maximize the power of a statistical test distinguishing between competing regression models. This article explores the use of T-optimality in the context of non-nested models, which do not share a common parameter space. We present the mathematical formulation, discuss its statistical properties, provide algorithmic considerations, and illustrate with numerical examples. Applications span medicine, engineering, and economics, where selecting the best predictive model is crucial.
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