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Passing-Bablok regression is a standard tool for method and assay comparisonstudies thanks to its place in industry guidelines such as CLSI. Unfortunately,its computational cost is high as a naive approach requires O(n2) time. Thismakes it impossible to compute the Passing-Bablok regression estimator on largedatasets. Additionally, even on smaller datasets it can be difficult to performbootstrap-based inference. We introduce the first quasilinear time algorithmfor the equivariant Passing-Bablok estimator. In contrast to the naivealgorithm, our algorithm runs in O(n log(n)) expected time using O(n) space,allowing for its application to much larger data sets. Additionally, weintroduce a fast estimator for the variance of the Passing-Bablok slope anddiscuss statistical inference based on bootstrap and this variance estimate.Finally, we propose a diagnostic plot to identify influential points inPassing-Bablok regression. The superior performance of the proposed methods isillustrated on real data examples of clinical method comparison studies.

Equivariant Passing-Bablok regression in quasilinear time