Effect Sizes for Equivalence Testing: Incorporating the Equivalence Interval

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dc.contributor.advisorCribbie, Robert A.
dc.contributor.authorMartinez Gutierrez, Naomi
dc.date.accessioned2021-11-15T15:22:48Z
dc.date.available2021-11-15T15:22:48Z
dc.date.copyright2021-06
dc.date.issued2021-11-15
dc.date.updated2021-11-15T15:22:48Z
dc.degree.disciplinePsychology (Functional Area: Quantitative Methods)
dc.degree.levelMaster's
dc.degree.nameMA - Master of Arts
dc.description.abstractEquivalence testing (ET) is a framework to determine if an effect is small enough to be considered meaningless, wherein meaningless is expressed as an equivalence interval (EI). Although traditional effect sizes (ESs) are important accompaniments to ET, these measures exclude information about the EI. Incorporating the EI is valuable for quantifying how far the effect is from the EI bounds. An ES measure we propose is the proportional distance (PD) from an observed effect to the smallest effect that would render it meaningful. We conducted two Monte Carlo simulations to evaluate the PD when applied to (1) mean differences and (2) correlations. The coverage rate and bias of the PD were excellent within the investigated conditions. We also applied the PD to two recent psychological studies. These applied examples revealed the beneficial properties of the PD, namely its ability to supply information above and beyond other statistical tests and ESs.
dc.identifier.urihttp://hdl.handle.net/10315/38693
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectStatistics
dc.subject.keywordsPsychology
dc.subject.keywordsQuantitative Methods
dc.subject.keywordsEquivalence Testing
dc.subject.keywordsProportional Distance
dc.subject.keywordsEffect Size
dc.titleEffect Sizes for Equivalence Testing: Incorporating the Equivalence Interval
dc.typeElectronic Thesis or Dissertation

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