Algorithm optimization enhances reference intervals in data sets, suggesting improved accuracy in results.
Objectives There are currently two publicly available R packages for the indirect determination of reference intervals: reflimR and refineR. We aimed to optimize the reflimR algorithm to achieve greater concordance with refineR, including in challenging data sets. Methods We modified the truncation algorithm of the three-stage reflimR method so that the approximation to the central 95 % of the presumably non-pathological values is performed consecutively in five steps rather than all at once. Results Using the livertests dataset included in the reflimR package as an example, we demonstrate that our refined approach can effectively handle datasets containing a substantial proportion of pathological values near the reference limit. The results are more robust and coincide better with the refineR results. Conclusions The updated reflimR version 1.1.0 is available on CRAN (Comprehensive R Archive Network) and delivers reliable results in an extremely short time with moderate requirements for the number of cases.
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Klawitter et al. (2025) studied this question.
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