Beyond the t-Test: Statistical Equivalence Testing

Abstract

Statistical Equivalence Testing BEYONDO ne of the most common questions considered by analytical chemists is whether replicate measurements are the same or significantly different from each other.The determination of significantly different results can be used to argue that a phenomenon is novel or to justify a claim of a significant improvement in a technique, process, or product.Science and technology are also driven by determinations of sameness, such as equivalence, control, or ruggedness.Given the variability inherent to most instrument systems, the question of whether a measurable difference is "real" can be difficult to answer.In some cases, intuition, experience, and knowledge of the practical context of the data can be used to inspect or "eyeball" the data to assess whether a true difference exists.For example, most of us would agree that a difference of 100% in a measurement that typically exhibits a precision of 1% is a real difference, and we would also agree that a difference of 0.01% is not significant for the same measurement.But what about less clear-cut cases in which the difference between two sets of data is similar to the precision?How much difference is "too much"?Not only does simple inspection fail in these circumstances, but a subjective process can be biased, is difficult to justify, and, most importantly, can lead to the wrong conclusion.

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