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Three-Sided Testing to Establish Practical Significance: A Tutorial

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Abstract

Researchers may want to know whether an observed statistical relationship is either meaningfully negative, meaningfully positive, or small enough to be considered practically equivalent to zero. Such a question cannot be addressed with standard null hypothesis significance testing or standard equivalence testing. Three-sided testing (TST) is a procedure to address such questions by simultaneously testing whether a relationship is significantly bounded below, within, or above predetermined smallest effect sizes of interest. TST is a natural extension of the standard procedure of two one-sided tests (TOST) for equivalence testing. TST offers a more comprehensive decision framework than TOST with no penalty to error rates or statistical power. In this article, we give a nontechnical introduction to TST; provide commands for conducting TST in R, Jamovi, and Stata; and provide a Shiny app for easy implementation. Whenever a meaningful smallest effect size of interest can be specified, TST should be combined with null hypothesis significance testing as a standard frequentist testing procedure.

Original languageEnglish
Pages (from-to)1-20
Number of pages20
JournalAdvances in Methods and Practices in Psychological Science
Volume9
Issue number2
DOIs
Publication statusPublished - Jun 2026

Bibliographical note

Publisher Copyright:
© The Author(s) 2026. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Keywords

  • equivalence test
  • hypothesis test
  • Jamovi
  • NHST
  • open materials
  • R
  • SESOI
  • Stata
  • three-sided testing
  • TOST
  • TST
  • tutorial

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