What is a tost test?
The TOST (two one-sided test) is a test of equivalence that is based on the classical t test used to test the hypothesis of equality between two means. So we will have two samples, a theoretical difference between the means as well as a range within which we can say that the sample means are equivalent.
How do you perform a tost?
A very simple equivalence testing approach is the “two one-sided tests” (TOST) procedure (Schuirmann, 1987). In the TOST procedure, an upper (ΔU) and lower (−ΔL) equivalence bound is specified based on the smallest effect size of interest (SESOI; e.g., a positive or negative difference of d = . 3).
How is statistical equivalence calculated?
When we refer to values as being “statistically equivalent” or to a “conclusion of statistical equivalence,” we mean the difference between groups is smaller than what is considered meaningful and statistically falls within the interval indicated by the equivalence bounds. In any one-sided test, for an alpha level of .
How is the Tost test used in Excel?
TOST (Equivalence test) is used to validate the equivalence of two means. Run equivalence tests in Excel using the XLSTAT add-on statistical software.
When to use Tost for an equivalence test?
The TOST approach can also be used for a one-sample test (and similarly for a two dependent sample test). In this case, we test the equivalence between the mean of a single population and some hypothetical mean μ0. This time we conduct two one-sample t-tests.
How does the equivalence test work in Excel?
Equivalence testing determines an interval where the means can be considered equivalent. The Equivalence Test uses two t-tests assuming equal variances with a hypothesized mean difference (u 1-u 2 = interval). Note: Excel does not do equivalence tests; QI Macros adds this functionality.
How are two one sided tests used in equivalence testing?
Traditional hypothesis testing seeks to determine if means are the same or different, but it can have false positives. Equivalence testing determines an interval where the means can be considered equivalent. The Two One-Sided Test uses two t-tests assuming equal variances with a hypothesized mean difference (u1 – u2 = interval).