Trials and Tribulations of Teaching Null Hypothesis Significance Testing in the Health Sciences

P. Sedgwick
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Abstract

Null hypothesis significance testing (NHST) has become the cornerstone of decision-making in clinical and healthcare research. Statistical significance (p < 0.05) is considered the gold standard for inferring that contextual significance exists. However, such practice is controversial since it was never intended for contextual significance to be inferred based on statistical significance. There have been frequent calls for the abandonment of NHST incorporating the bright-line rule of p < 0.05. The call for a statistics reform represents challenges for the teaching of statistics in the Health Sciences. NHST and p-values are central to traditional undergraduate and postgraduate curricula. It is suggested that whatever the future for NHST, it still needs to be taught. It is important that students appreciate the challenges that inferences based on NHST pose. To avoid such challenges in the future, a greater understanding of the underlying statistical principles is needed. Curricula are typically lacking in these principles, whilst they are difficult concepts based on probability and uncertainty. This may have contributed to the controversial practice of inferring contextual significance from statistical significance. A framework for the teaching of NHST and p-values is presented.
健康科学教学中零假设显著性检验的尝试与磨难
零假设显著性检验(NHST)已成为临床和医疗保健研究决策的基石。统计显著性(p < 0.05)被认为是推断上下文显著性存在的黄金标准。然而,这种做法是有争议的,因为它从来没有打算根据统计显著性来推断上下文意义。经常有人呼吁放弃包含p < 0.05明线规则的NHST。统计改革的呼声对卫生科学统计教学提出了挑战。NHST和p值是传统本科和研究生课程的核心。有人建议,无论NHST的未来如何,它仍然需要教授。让学生认识到基于NHST的推理所带来的挑战是很重要的。为了避免未来出现这样的挑战,需要对基本的统计原理有更深入的了解。课程通常缺乏这些原则,而它们是基于概率和不确定性的困难概念。这可能促成了从统计显著性推断上下文意义的有争议的实践。提出了NHST和p值教学的框架。
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