Equivalence test

An equivalence test is a test that allows to conclude, with a specified confidence level, equivalence between observations.

When using equivalence tests, you must specify how large of a difference between group averages would represent a clinically or practically important (significant) difference, or how large a difference can be to be still considered insignificant. These limits must be decided beforehand and are based on scientific and clinical judgment, or industry-specific standards.

Equivalence may be concluded when the observed differences are smaller than the pre-specified maximum insignificant differences. When differences are larger than the pre-specified limits, equivalence is rejected.

In MedCalc, Schuirmann’s (1987) "two one-sided tests" (TOST) approach can be used to test equivalence. To do this, you

  • define the range of differences that are not clinically or practically important (i.e. not significant)
  • depending on the experimental design, use the Independent samples t-test or Paired samples t-test
  • select the option for a 90% (!) Confidence Interval
  • if the entire range of the 90% Confidence Interval of the mean difference lies within prespecified range of indifference, then conclude with 95% confidence that the two treatments are equivalent.

Literature

  • Schuirmann DJ (1987) A comparison of the Two One-Sided Tests Procedure and the Power Approach for assessing the equivalence of average bioavailability. Journal of Pharmacokinetics and Biopharmaceutics 15:657-680.

See also

External links

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