Distribution-free hyperrectangular tolerance regions for setting multivariate reference regions in laboratory medicine
Distribution-free hyperrectangular tolerance regions for setting multivariate reference regions in laboratory medicine
Reference regions are important in laboratory medicine to interpret the test results of patients, and usually given by tolerance regions. Tolerance regions of p (>= 2) dimensions are highly desirable when the test results contains p outcome measures. Nonparametric hyperrectangular tolerance regions are attractive in real problems due to their robustness with respect to the underlying distribution of the measurements and ease of intepretation, and methods to construct them have been recently provided by Young and Mathew [1]. However, their validity is supported by a simulation study only. In this paper, nonparametric hyperrectangular tolerance regions are constructed by using Tukey's [2,3] elegant results of equivalence blocks. The validity of these new tolerance regions is proven mathematically in [2,3] under the only assumption that the underlying distribution of the measurements is continuous. The methodology is applied to analyze the kidney function problem considered in Young and Mathew [1]
Liu, Wei
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Bretz, Frank
aa8a675f-f53f-4c50-8931-8e9b7febd9f0
Cortina-Borja, Mario
028ebae2-003d-413b-95cc-47d76914b006
Liu, Wei
b64150aa-d935-4209-804d-24c1b97e024a
Bretz, Frank
aa8a675f-f53f-4c50-8931-8e9b7febd9f0
Cortina-Borja, Mario
028ebae2-003d-413b-95cc-47d76914b006
Liu, Wei, Bretz, Frank and Cortina-Borja, Mario
(2023)
Distribution-free hyperrectangular tolerance regions for setting multivariate reference regions in laboratory medicine.
Statistics in Medicine.
(In Press)
Abstract
Reference regions are important in laboratory medicine to interpret the test results of patients, and usually given by tolerance regions. Tolerance regions of p (>= 2) dimensions are highly desirable when the test results contains p outcome measures. Nonparametric hyperrectangular tolerance regions are attractive in real problems due to their robustness with respect to the underlying distribution of the measurements and ease of intepretation, and methods to construct them have been recently provided by Young and Mathew [1]. However, their validity is supported by a simulation study only. In this paper, nonparametric hyperrectangular tolerance regions are constructed by using Tukey's [2,3] elegant results of equivalence blocks. The validity of these new tolerance regions is proven mathematically in [2,3] under the only assumption that the underlying distribution of the measurements is continuous. The methodology is applied to analyze the kidney function problem considered in Young and Mathew [1]
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Distribution-free hyperrectangular tolerance regions for setting multivariate reference regions in laboratory medicine
- Accepted Manuscript
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Accepted/In Press date: 23 September 2023
Identifiers
Local EPrints ID: 482882
URI: http://eprints.soton.ac.uk/id/eprint/482882
ISSN: 0277-6715
PURE UUID: 8a07ffdb-7977-4cb2-8fdb-d95efd1817cb
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Date deposited: 16 Oct 2023 16:47
Last modified: 23 Sep 2024 04:01
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Author:
Frank Bretz
Author:
Mario Cortina-Borja
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