Testing Equivalence in Communication Research: Theory and Application

Although equivalence testing is preferred when a researcher's goal is to support the null hypothesis (i.e., no substantial effect), equivalence tests are virtually unknown and unused in the communication field. This article provides the rationale for and theoretical background of equivalence testing and offers examples of equivalence tests for the independent and dependent groups t-test and tests of association using Pearson's coefficient or correlation. From a review of meta-analyses, we provide tables of commonly observed effect-sizes across subdisciplines and topic areas in communication and offer these as a guideline for choosing minimum substantial effects (Δ) in equivalence testing when no other information source is available. To facilitate the adoption of equivalence tests in future research, we provide easy-to-use custom dialogs for SPSS which greatly simplify their computation and application.