Parametric and nonparametric improvements in Bland and Altman's assessment of agreement method

Lin An Chen, Chu-Lan Kao*

*此作品的通信作者

研究成果: Article同行評審

7 引文 斯高帕斯(Scopus)

摘要

The Bland-Altman method, which assesses agreement via an assessment set constructed by the difference of the measurement variables, has received great attention. Other assessment approaches have been proposed following the same difference-based framework. However, the exact assessment set constructed by the difference is achievable only for measurements with certain joint distributions. To provide a more general assessment framework, we propose two approaches. First, when the measurement distribution is known, we propose a parametric approach that constructs the assessment set through a measure of closeness corresponding to the distribution. Second, when the measurement distribution is unknown, we propose a nonparametric approach that constructs the assessment set through quantile regression. Both approaches quantify the degree of agreement with the presence of both systematic and random measurement errors, and enable one to go beyond the difference-based approach. Results of simulation and data analyses are presented to compare the two approaches.

原文English
頁(從 - 到)2155-2176
頁數22
期刊Statistics in Medicine
40
發行號9
DOIs
出版狀態Published - 30 4月 2021

指紋

深入研究「Parametric and nonparametric improvements in Bland and Altman's assessment of agreement method」主題。共同形成了獨特的指紋。

引用此