Abstract
BACKGROUND: ML-NMR provides a framework for defining an individual-level regression model, which is integrated over aggregate populations to form an aggregate-level model. ML-NMR avoids aggregation bias and produces estimates in any target population. ML-NMR has been published and applied to binary outcomes, but not time-to-event outcomes.
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