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Stats, Volume 7, Issue 4
December 2024 - 27 articles
Cover Story: Reference intervals are indispensable for the interpretation of medical laboratory results to distinguish “normal” from “pathological” values. Indirect methods can be used to estimate the reference intervals from a mixture of normal and pathological values. For some analytes, a significant proportion of the measurements fall below the limit of detection (LOD), such that only the information where they are smaller than the LOD is available. While standard statistical methods for reference interval estimation cannot handle values below the LOD, we propose a quantile- and a maximum likelihood-based estimator to solve this problem. Theoretical analyses, simulation experiments, and real data show that our approach yields good estimates for the reference interval, even when a substantial proportion of values lies below the LOD. View this paper
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Stats - ISSN 2571-905X