Tolerance interval testing for assessing accuracy and precision simultaneously

Tolerance intervals have been recommended for simultaneously validating both the accuracy and precision of an analytical procedure. However, statistical inferences for the corresponding hypothesis testing are scarce. The aim of this study is to establish a whole statistical inference for tolerance interval testing, including sample size determination, power analysis, and calculation of p-value. More specifically, the proposed method considers the bounds of a tolerance interval as random variables so that a bivariate distribution can be derived. Simulations confirm the theoretical properties of the method. Furthermore, an example is used to illustrate the proposed method.