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.

摘要

本文讨论了“强式”常客测试作为通信科学中零假设检验的有用补充。在“强形式”设置中，研究人员定义了（最小）理论兴趣的假设效应大小，并评估她的发现在多大程度上证伪或证实了该特定假设。我们认为“强形式”测试的想法与科学改革运动的理想密切相关，在一般线性模型的背景下讨论其技术应用，并展示相关的P-可以计算和解释类似值的数量。我们还提供示例和模拟来说明强形式设置如何需要对研究结果进行更细致的思考。此外，我们还讨论了一些可能仍然阻碍强式测试广泛采用的陷阱。