1.1 本规程提供了统计方法，用于对来自两个来源的数值数据进行等效测试，以确定其真实均值或方差的差异是否不超过预定限值。 1.2 应用包括 (1) 与可接受参考值的偏差等效性测试， (2) 确定是指实验室内两种试验方法、试验装置、仪器、试剂源或操作员的等效性，或方法转移中两个实验室的等效性，以及 (3) 确定改进试验程序相对于当前试验程序在性能特性方面的非劣性。 1.3 本标准中的指南适用于在给定测试结果水平下对单一材料或涵盖选定测试结果范围的多种材料进行的实验。 1.4 为确定等效性试验所需的数据量提供了指导。讨论了与等价决策相关的风险控制。 1.5 以国际单位制表示的数值应视为标准值。本标准不包括其他计量单位。 1.6 本标准并非旨在解决与其使用相关的所有安全问题（如有）。本标准的用户有责任在使用前制定适当的安全、健康和环境实践，并确定监管限制的适用性。 1.7 本国际标准是根据世界贸易组织技术性贸易壁垒（TBT）委员会发布的《关于制定国际标准、指南和建议的原则的决定》中确立的国际公认标准化原则制定的。 ====意义和用途====== 4.1 进行常规测试的实验室继续需要改进其测试过程。在这些情况下，必须证明任何变化既不会导致当前测试过程的测试结果发生不希望的变化，也不会实质性地影响测试结果 性能特点 试验方法。本标准提供了所需的实验和统计方法指南，以证明修改后的测试过程的测试结果与当前测试过程的测试结果等效，其中 等价性 定义为在规定限制内的协议，称为 等效极限 . 4.1.1 等效极限表示最坏情况下的差异或比率，在等效测试之前确定，其值通常由主题专家协商确定。 4.1.2 测试过程的修改示例包括但不限于以下内容: (1) 试验方法程序步骤中操作水平的变化， (2) 安装新仪器、装置或试剂和测试材料来源， (3) 评估执行测试的新人员，以及 (4) 将测试转移到新地点。 4.1.3 直接适用于测试方法的性能特征示例包括偏差、精度、灵敏度、特异性、线性和范围。 其他特征是执行测试程序所需的测试成本和运行时间。 4.2 等效性测试通过设计实验进行，该实验根据常规测试的相同类型材料的修改和当前测试程序生成测试结果。实验设计取决于所需的等效类型，如下所述。第节讨论了各种目标的实验设计和执行 5. . 4.2.1 平均值等效 涉及由于测试过程中的修改，平均测试结果在任何方向上的潜在变化。测试结果是在重复性条件下，通过相同材料上的修改和当前测试过程生成的，并评估其平均测试结果的差异。 4.2.1.1 在无法在重复性条件下进行测试的情况下，例如使用在线仪器，可以根据修改后的测试过程和当前测试过程中的成对测试结果生成测试结果，并评估成对测试结果之间的平均差异。 4.2.2 范围等效 在选定的更广泛的测试结果范围内评估均值差异，实验使用覆盖该范围的材料。计算了两个测试程序的测试结果之间的线性统计关系的斜率。如果斜率等于值1（1），则两个测试过程满足斜率等效。斜率等价和均值等价的结合定义了范围等价。 4.2.3 偏置等效 是应用于性能特征的均值等价的特例。在具有可接受参考值（ARV）的认证标准物质（CRM）上生成一组测试结果，以评估当前测试程序的测试方法偏差。然后将平均测试结果与ARV进行比较，以估计已知偏差的发生。 4.2.4 非劣性 仅在改良测试程序与当前测试程序的性能特征的劣化结果方向上存在差异。 非劣性可能涉及均值、标准差或其他统计参数的比较。 4.2.4.1 非劣性测试可能涉及修改后的程序和当前程序之间性能特征的权衡。例如，修改后的过程在分析灵敏度或精度方面可能略低于已建立的过程，但可能具有抵消优势，例如更快地交付测试结果或降低测试成本。 4.3 风险管理- 为确定在接受或拒绝等效时做出错误决策的风险控制所需的数据量提供了指导（参见 5.4 和截面 X1.2 ). 4.3.1 这个 消费者风险 是错误声明等价的风险。与该风险相关的概率直接控制在较低的水平，因此接受等效性可以高度保证真实差异小于等效极限。 4.3.2 这个 生产者风险 是错误拒绝对等的风险。与该风险相关的概率由实验生成的数据量控制。如果等效性测试拒绝了有效的改进，这可能会导致公司及其实验室（生产商）的机会损失，或在改进测试过程中造成不必要的额外努力。

1.1 This practice provides statistical methodology for conducting equivalence testing on numerical data from two sources to determine if their true means or variances differ by no more than predetermined limits. 1.2 Applications include (1) equivalence testing for bias against an accepted reference value, (2) determining means equivalence of two test methods, test apparatus, instruments, reagent sources, or operators within a laboratory or equivalence of two laboratories in a method transfer, and (3) determining non-inferiority of a modified test procedure versus a current test procedure with respect to a performance characteristic. 1.3 The guidance in this standard applies to experiments conducted on a single material at a given level of the test result or on multiple materials covering a range of selected test results. 1.4 Guidance is given for determining the amount of data required for an equivalence trial. The control of risks associated with the equivalence decision is discussed. 1.5 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard. 1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use. 1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ====== 4.1 Laboratories conducting routine testing have a continuing need to make improvements in their testing processes. In these situations it must be demonstrated that any changes will neither cause an undesirable shift in the test results from the current testing process nor substantially affect a performance characteristic of the test method. This standard provides guidance on experiments and statistical methods needed to demonstrate that the test results from a modified testing process are equivalent to those from the current testing process, where equivalence is defined as agreement within a prescribed limit, termed an equivalence limit . 4.1.1 The equivalence limit, which represents a worst-case difference or ratio, is determined prior to the equivalence test and its value is usually set by consensus among subject-matter experts. 4.1.2 Examples of modifications to the testing process include, but are not limited, to the following: (1) Changes to operating levels in the steps of the test method procedure, (2) Installation of new instruments, apparatus, or sources of reagents and test materials, (3) Evaluation of new personnel performing the testing, and (4) Transfer of testing to a new location. 4.1.3 Examples of performance characteristics directly applicable to the test method include bias, precision, sensitivity, specificity, linearity, and range. Additional characteristics are test cost and elapsed time needed to conduct the test procedure. 4.2 Equivalence testing is performed by a designed experiment that generates test results from the modified and current testing procedures on the same types of materials that are routinely tested. The design of the experiment depends on the type of equivalence needed as discussed below. Experiment design and execution for various objectives is discussed in Section 5 . 4.2.1 Means equivalence is concerned with a potential shift in the mean test result in either direction due to a modification in the testing process. Test results are generated under repeatability conditions by the modified and current testing processes on the same material, and the difference in their mean test results is evaluated. 4.2.1.1 In situations where testing cannot be conducted under repeatability conditions, such as using in-line instrumentation, test results may be generated in pairs of test results from the modified and current testing processes, and the mean differences among paired test results are evaluated. 4.2.2 Range equivalence evaluates the differences in means over a selected wider range of test results and the experiment uses materials that cover that range. The slope of the linear statistical relationship between the test results from the two testing procedures is calculated. If the slope is equivalent to the value one (1), then the two testing processes meet slope equivalence. The combination of slope equivalence and means equivalence defines range equivalence. 4.2.3 Bias equivalence is a special case of means equivalence applied to a performance characteristic. A single set of test results is generated on a certified reference material (CRM) having an accepted reference value (ARV) to evaluate the test method bias of the current testing procedure. The mean test result is then compared with the ARV to estimate the occurrence of a known bias. 4.2.4 Non-inferiority is concerned with a difference only in the direction of an inferior outcome in a performance characteristic of the modified testing procedure versus the current testing procedure. Non-inferiority may involve the comparisons of means, standard deviations, or other statistical parameters. 4.2.4.1 Non-inferiority testing may involve trade-offs in performance characteristics between the modified and current procedures. For example, the modified process may be slightly inferior to the established process with respect to assay sensitivity or precision but may have off-setting advantages such as faster delivery of test results or lower testing costs. 4.3 Risk Management— Guidance is provided for determining the amount of data required to control the risks of making the wrong decision in accepting or rejecting equivalence (see 5.4 and Section X1.2 ). 4.3.1 The consumer’s risk is the risk of falsely declaring equivalence. The probability associated with this risk is directly controlled to a low level so that accepting equivalence gives a high degree of assurance that the true difference is less than the equivalence limit. 4.3.2 The producer’s risk is the risk of falsely rejecting equivalence. The probability associated with this risk is controlled by the amount of data generated by the experiment. If valid improvements are rejected by equivalence testing, this can lead to opportunity losses to the company and its laboratories (the producers) or cause unnecessary additional effort in improving the testing process.