While Null Hypothesis Significance Testing (NHST) remains a widely used statistical tool, it suffers from several shortcomings, such as conflating statistical and practical significance, sensitivity to sample size, and the inability to distinguish between accepting the null hypothesis and failing to reject it. Recent efforts have focused on developing alternatives to NHST to address these issues. Despite these efforts, conventional NHST remains dominant in scientific research due to its simplicity and perceived ease of interpretation. Our work presents a novel alternative to NHST that is just as accessible and intuitive: REACT. It not only tackles the shortcomings of NHST but also offers additional advantages over existing alternatives. For instance, REACT is easily applicable to multiparametric hypotheses and does not require stringent significance-level corrections when conducting multiple tests. We illustrate the practical utility of REACT through real-world data examples, using criteria aligned with common research practices to distinguish between the absence of evidence and evidence of absence.

翻译：尽管零假设显著性检验（NHST）仍是一种广泛使用的统计工具，但它存在若干缺陷，例如将统计显著性与实际显著性混为一谈、对样本量敏感，以及无法区分接受零假设与未能拒绝零假设。近年来，研究者致力于开发NHST的替代方案以解决这些问题。然而，由于NHST的简便性和直观性，它在科学研究中仍占据主导地位。我们提出了一种同样易于使用且直观的新替代方案：REACT。它不仅克服了NHST的缺陷，还比现有替代方案具有更多优势。例如，REACT可轻松应用于多参数假设检验，且在进行多重检验时无需严格的显著性水平校正。我们通过实际数据示例展示了REACT的实用性，并采用与常见研究实践一致的标准来区分“缺乏证据”与“证据缺失”。