Strong-Form Frequentist Testing In Communication Science: Principles, Opportunities, And Challenges

Lennert Coenen, Tim Smits

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper discusses ‘strong-form’ frequentist testing as a useful complement to null hypothesis testing in communication science. In a ‘strong-form’ set-up a researcher defines a hypothetical effect size of (minimal) theoretical interest and assesses to what extent her findings falsify or corroborate that particular hypothesis. We argue that the idea of ‘strong-form’ testing aligns closely with the ideals of the movements for scientific reform, discuss its technical application within the context of the General Linear Model, and show how the relevant P-value-like quantities can be calculated and interpreted. We also provide examples and a simulation to illustrate how a strong-form set-up requires more nuanced reflections about research findings. In addition, we discuss some pitfalls that might still hold back strong-form tests from widespread adoption.

Original languageEnglish
Pages (from-to)237-265
Number of pages29
JournalCommunication Methods & Measures
Volume16
Issue number4
DOIs
Publication statusPublished - 9 Sept 2022

Keywords

  • CONFIDENCE-INTERVALS
  • EFFECT SIZE
  • HYPOTHESIS
  • P-VALUES
  • POWER

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