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Title: The difference between “equivalent” and “not different”

Often, experimenters 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 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.
Authors:
 [1] ;  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Statistical Sciences Group
  2. Arizona State Univ., Phoenix, AZ (United States). School of Mathematical and Natural Sciences
Publication Date:
OSTI Identifier:
1224047
Report Number(s):
LA-UR--15-20072
Journal ID: ISSN 0898-2112
Grant/Contract Number:
AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
Quality Engineering
Additional Journal Information:
Journal Volume: 2015; Journal Issue: 3; Journal ID: ISSN 0898-2112
Publisher:
American Society for Quality Control
Research Org:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING Mathematics