论文标题
quasilIrinear时间中的模棱两可的传球回归
Equivariant Passing-Bablok regression in quasilinear time
论文作者
论文摘要
通过Bablok回归是方法和测定比较研究的标准工具，这要归功于其在CLSI等行业指南中的地位。不幸的是，它的计算成本很高，因为一种天真的方法需要O（n2）时间。这使得无法计算大型数据集上的传递Bablok回归估计器。此外，即使在较小的数据集上，也很难执行基于自举的推断。我们介绍了模棱两可的传球估计器的第一个准线性时间算法。与天真算法相反，我们的算法在使用O（n）空间的O（n log（n））预期时间中运行，从而使其应用于更大的数据集。此外，我们引入了一个快速的估计器，以了解传球斜率的方差，并根据引导程序和此方差估算讨论统计推断。最后，我们提出了一个诊断图，以识别传递Bablok回归中的影响点。在临床方法比较研究的实际数据示例中说明了所提出方法的出色性能。
Passing-Bablok regression is a standard tool for method and assay comparison studies thanks to its place in industry guidelines such as CLSI. Unfortunately, its computational cost is high as a naive approach requires O(n2) time. This makes it impossible to compute the Passing-Bablok regression estimator on large datasets. Additionally, even on smaller datasets it can be difficult to perform bootstrap-based inference. We introduce the first quasilinear time algorithm for the equivariant Passing-Bablok estimator. In contrast to the naive algorithm, our algorithm runs in O(n log(n)) expected time using O(n) space, allowing for its application to much larger data sets. Additionally, we introduce a fast estimator for the variance of the Passing-Bablok slope and discuss statistical inference based on bootstrap and this variance estimate. Finally, we propose a diagnostic plot to identify influential points in Passing-Bablok regression. The superior performance of the proposed methods is illustrated on real data examples of clinical method comparison studies.
