Bland-Altman 图形法在没有对准确性、精确性和一致性进行推断时是否有用？
Is Bland-Altman plot method useful without inference for accuracy, precision, and agreement?
AI总结：
本文提出基于结构回归的三个嵌套检验，为测量技术等价性提供推断统计支持，评估准确性、精确性和一致性，并通过五个数据集验证其有效性，同时提供R包以实现图形化交流与稳健统计推断。
摘要：
目的：Bland and Altman plot method 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价性，通常旨在用一种新的、侵入性更小或更便宜的技术替代传统技术。尽管易于交流，但由于缺乏合适的推断统计支持，Bland and Altman plot 经常被误读。常见的替代方法，如 Pearson's correlation 或 ordinal least-square linear regression，也无法定位每种测量技术的弱点。方法：在此，我们基于结构回归提出了三个嵌套检验，为测量技术间的等价性提供推断统计支持，以评估结构均值的等价性（准确性）、结构方差的等价性（精确性），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 bootstrapping 的稳健方法。图形输出也得以实现，遵循 Bland and Altman 的原则以便于交流。结果：展示了该方法的表现，并与之前发表的应用 Bland and Altman 方法的五个数据集进行了对比。一个案例展示了严格等价，三个案例展示了部分等价，一个展示了较差的等价。开发的 R 包包含开放代码和数据，可在 Harvard Dataverse 免费获取安装说明：https://doi.org/10.7910/DVN/AGJPZH。结论：可以测试两种技术是否具有完全等价性，同时保留 Bland and Altman 原则的图形交流，并增加稳健且合适的推断统计。将等价性分解为准确性、精确性和一致性有助于定位问题来源，从而改进新技术。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
