Objective: Bland and Altman plot method is a widely cited and applied graphical approach for assessing the equivalence of quantitative measurement techniques, usually aiming to replace a traditional technique with a new, less invasive, or less expensive one. Although easy to communicate, Bland and Altman plot is often misinterpreted by lacking suitable inferential statistical support. Usual alternatives, such as Pearson's correlation or ordinal least-square linear regression, also fail to locate the weakness of each measurement technique. Method: Here, inferential statistics support for equivalence between measurement techniques is proposed in three nested tests based on structural regressions to assess the equivalence of structural means (accuracy), the equivalence of structural variances (precision), and concordance with the structural bisector line (agreement in measurements obtained from the same subject), by analytical methods and robust approach by bootstrapping. Graphical outputs are also implemented to follow Bland and Altman's principles for easy communication. Results: The performance of this method is shown and confronted with five data sets from previously published articles that applied Bland and Altman's method. One case demonstrated strict equivalence, three cases showed partial equivalence, and one showed poor equivalence. The developed R package containing open codes and data are available with installation instructions for free distribution at Harvard Dataverse at https://doi.org/10.7910/DVN/AGJPZH. It is possible to test whether two techniques may have full equivalence, preserving graphical communication according to Bland and Altman's principles, but adding robust and suitable inferential statistics. Decomposing the equivalence in accuracy, precision, and agreement helps the location of the source of the problem in order to fix a new technique.

翻译：目的：布兰德-阿尔特曼绘图法是一种被广泛引用和应用的图形化方法，用于评估定量测量技术的等效性，通常旨在用新的、侵入性较小或成本较低的技术替代传统技术。尽管易于沟通，但布兰德-阿尔特曼图常因缺乏适当的推断性统计支持而被误解。常见的替代方法，如皮尔逊相关性或普通最小二乘法线性回归，也无法定位每种测量技术的弱点。方法：本文基于结构回归提出了三种嵌套检验，为测量技术间的等效性提供推断性统计支持，以评估结构均值的等效性（准确性）、结构方差的等效性（精密度）以及与结构平分线的一致性（同一受试者测量结果的一致性），采用解析方法和基于自助法的稳健方法。同时实现了图形输出，以遵循布兰德-阿尔特曼原则，便于沟通。结果：展示了该方法的性能，并与以往应用布兰德-阿尔特曼方法的五组已发表文章数据集进行了对比。一个案例显示了严格等效性，三个案例显示了部分等效性，一个案例显示了较差的等效性。开发的R软件包包含开放代码和数据，附带安装说明，可在哈佛数据空间（https://doi.org/10.7910/DVN/AGJPZH）免费获取。该方法能够检验两种技术是否具有完全等效性，在保留布兰德-阿尔特曼原则的图形化沟通基础上，增加了稳健且适当的推断性统计。将等效性分解为准确性、精密度和一致性，有助于定位问题根源，以便改进新技术。