The difference between “equivalent” and “not different”

Christine M. Anderson-Cook, Connie M. Borror

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Experimenters frequently wish to establish that populations of units can be considered equivalent to each other, in order to leverage improved knowledge about one population for characterizing the new population or to establish the comparability of items. Equivalence tests have existed for many years, but their use in industry seems to have been largely restricted to biomedical applications, such as for assessing the equivalence of two drugs or protocols. We present the fundamentals of equivalence tests, compare them to traditional two-sample and analysis of variance (ANOVA) tests that are better suited to establishing differences in populations, and propose the use of a graphical summary to compare p values across different thresholds of practically important differences. The methods are illustrated using an example.

Original languageEnglish (US)
JournalQuality Engineering
DOIs
StateAccepted/In press - Oct 23 2015

Fingerprint

Analysis of variance (ANOVA)
Industry

Keywords

  • bioequivalence
  • equivalence test
  • hypothesis testing
  • power
  • practically accepted difference
  • same versus different
  • sample size
  • standards testing
  • threshold for indifference zone

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering

Cite this

The difference between “equivalent” and “not different”. / Anderson-Cook, Christine M.; Borror, Connie M.

In: Quality Engineering, 23.10.2015.

Research output: Contribution to journalArticle

Anderson-Cook, Christine M. ; Borror, Connie M. / The difference between “equivalent” and “not different”. In: Quality Engineering. 2015.
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