Abstract

The diagnoses and clinical management of many reproductive health conditions rely on categorically interpreting hormone measurements as either within or outside a ‘normal’ reference range. Historically these ranges represent the 95% confidence intervals of a small population without regard to the distributional asymmetry expected by compositional data. We establish a more robust statistical framework that considers continuous quantiles, derived from a large dataset, in order to better define normal reference ranges of reproductive and thyroid hormone levels.

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