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) 确定实验室内两种测试方法、测试仪器、仪器、试剂源或操作员的等效性，以及 (3) 方法转移中两个实验室的等效性。 1.3 本标准中的当前指南仅适用于在单一材料上进行的实验。 为确定等效性试验所需的数据量提供了指导。 1.4 用于确定等效性的统计方法是两个单侧测试（TOST）程序。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和健康实践，并确定监管限制的适用性。 ====意义和用途====== 4.1 进行常规测试的实验室持续需要评估测试结果偏差，评估改进测试过程性能的变化，或验证将测试方法转移到新位置或设备。在所有情况下，必须证明任何偏差或创新对材料特性测试结果的影响可以忽略不计。本标准提供了统计方法，以确认测试过程的平均测试结果等同于参考标准或其他测试过程的平均测试结果，其中 等价性 定义为在规定范围内的协议，称为 等效极限 . 4.1.1 本规程中的实验室内应用包括但不限于以下内容: (1) 评估测试方法相对于认证标准物质的偏差， (2) 由于测试方法程序中的微小变化而产生的评估偏差， (3) 鉴定实验室中的新仪器、装置或操作员，以及 (4) 鉴定测试程序中使用的试剂或其他材料的新来源。 4.1.2 该实践还支持评估从开发实验室到接收实验室的方法转移中的系统差异。 4.2 这种做法目前只涉及人口平均数的等价性。在本标准中，a 人口 指由测量单个材料特性的稳定测试过程产生的一组假设测试结果。 注1: 等价概念也适用于均值以外的总体参数，例如精度，表示为方差、标准差或相对标准差（变异系数）、线性、灵敏度、特异性等。 4.3 在本实践中，人口平均数等效性测试的数据分析使用了一种称为“两个一”的统计方法- 应在本标准中详细描述的侧面试验（TOST）程序（见 X1.1 ). TOST程序将适用于所选的目标类型和实验设计。 4.3.1 历史上，该程序起源于制药行业，用于生物等效性试验 ( 1. , 2. ) , 3. 表示为双面测试程序，此后被用于其他应用，特别是在测试和测量应用中 ( 3. , 4. ) . 4.3.2 传统学生的 t 等效性测试不建议使用用于检测差异的测试，因为它不能正确控制消费者和生产者在此应用中的风险（请参阅 X1.3 ). 4.4 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 X1.2 ). 4.4.1 消费者风险是指当实际偏差或均值差异等于等效极限时，消费者接受等效的概率。这种可能性被控制在较低的水平，因此接受等效性可以高度保证所讨论的差异小于等效极限。 4.4.2 生产者的风险是错误拒绝等价物的风险。 如果改进被拒绝，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额外的不必要的努力。

1.1 This practice provides statistical methodology for conducting equivalence testing on numerical data from two sources to determine if their true means differ by no more than predetermined limits. 1.2 Applications include (1) equivalence testing for bias against an accepted reference value, (2) determining equivalence of two test methods, test apparatus, instruments, reagent sources, or operators within a laboratory, and (3) equivalence of two laboratories in a method transfer. 1.3 The current guidance in this standard applies only to experiments conducted on a single material. Guidance is given for determining the amount of data required for an equivalence trial. 1.4 The statistical methodology for determining equivalence used is the two one-sided tests (TOST) procedure. 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 and health practices and determine the applicability of regulatory limitations prior to use. ====== Significance And Use ====== 4.1 Laboratories conducting routine testing have a continuing need to evaluate test result bias, to evaluate changes for improving the test process performance, or to validate the transfer of a test method to a new location or apparatus. In all situations it must be demonstrated that any bias or innovation will have negligible effect on test results for a characteristic of a material. This standard provides statistical methods to confirm that the mean test results from a testing process are equivalent to those from a reference standard or another testing process, where equivalence is defined as agreement within prescribed limits, termed equivalence limits . 4.1.1 The intra-laboratory applications in this practice include, but are not limited to, the following: (1) Evaluating the bias of a test method with respect to a certified reference material, (2) Evaluating bias due to a minor change in a test method procedure, (3) Qualifying new instruments, apparatus, or operators in a laboratory, and (4) Qualifying new sources of reagents or other materials used in the test procedure. 4.1.2 This practice also supports evaluating systematic differences in a method transfer from a developing laboratory to a receiving laboratory. 4.2 This practice currently deals only with the equivalence of population means. In this standard, a population refers to a hypothetical set of test results arising from a stable testing process that measures a characteristic of a single material. Note 1: The equivalence concept can also apply to population parameters other than means, such as precision, stated as variances, standard deviations, or relative standard deviations (coefficients of variation), linearity, sensitivity, specificity, etc. 4.3 The data analysis for equivalence testing of population means in this practice uses a statistical methodology termed the two one-sided tests (TOST) procedure which shall be described in detail in this standard (see X1.1 ). The TOST procedure will be adapted to the type of objective and experiment design selected. 4.3.1 Historically, this procedure originated in the pharmaceutical industry for use in bioequivalence trials ( 1 , 2 ) , 3 denoted as the Two One-Sided Tests Procedure, and has since been adopted for other applications, particularly in testing and measurement applications ( 3 , 4 ) . 4.3.2 The conventional Student’s t test used for detecting differences is not recommended for equivalence testing as it does not properly control the consumer’s and producer’s risks for this application (see X1.3 ). 4.4 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 X1.2 ). 4.4.1 The consumer’s risk is the probability of accepting equivalence when the actual bias or difference in means is equal to the equivalence limit. This probability is controlled to a low level so that accepting equivalence gives a high degree of assurance that differences in question are less than the equivalence limit. 4.4.2 The producer’s risk is the risk of falsely rejecting equivalence. If improvements are rejected this can lead to opportunity losses to the company and its laboratories (the producers) or cause additional unnecessary effort in improving the testing process.