Strong-Form Frequentist Testing In Communication Science: Principles, Opportunities, And Challenges
Coenen,Lennert Smits,Tim
Coenen,Lennert
Smits,Tim
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.
Description
Funding Information: Lennert Coenen's contribution to the paper was made possible (in part) by his postdoctoral fellowship at the Research Foundation Flanders [12J7619N]. Publisher Copyright: © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC.
Date
2022-09-09
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Volume Title
Publisher
Research Projects
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Keywords
CONFIDENCE-INTERVALS, EFFECT SIZE, HYPOTHESIS, P-VALUES, POWER
Citation
Coenen, L & Smits, T 2022, 'Strong-Form Frequentist Testing In Communication Science : Principles, Opportunities, And Challenges', Communication Methods & Measures, vol. 16, no. 4, pp. 237-265. https://doi.org/10.1080/19312458.2022.2086690
License
info:eu-repo/semantics/openAccess