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.
4.2 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.
4.3 The data analysis for equivalence testing of population means in this practice uses a statistical methodology termed the “Two one-sided t-test” (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 Test, 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 This practice provides recommendations for the design of an equivalence experiment, and two basic designs are discussed. 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.
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.