论文标题
t分布的分布无效假设检验
Distributional Null Hypothesis Testing with the T distribution
论文作者
论文摘要
零假设的显着性检验（NHST）长期以来一直是科学项目的核心，指导理论发展并支持基于证据的干预和决策。然而，近年来，人们对NHST的严重问题的认识越来越普遍，因此，提出了限制使用NHST技术的建议，放弃这些技术并转向替代性统计方法，甚至完全禁止使用NHST。这些建议还为时过早，因为在许多情况下，观察到的NHST的问题都是出于偶然性和在许多情况下的选择而出现的：NHST对点形式无效的测试的选择。我们表明，针对分布而不是点形式的测试是在数学上和实验上更好地动机的，并且使用分布零是解决标准点形式NHST方法的许多问题。我们还表明，使用分布空的使用允许一种零假设检验的形式，该测试既考虑给定结果的统计显着性，又要考虑到复制的可能性，从而导致了新的实验。我们不应该放弃NHST，而应以更通用的形式使用NHST方法，而不是分配形式而不是点形式。
Null Hypothesis Significance Testing (NHST) has long been central to the scientific project, guiding theory development and supporting evidence-based intervention and decision-making. Recent years, however, have seen growing awareness of serious problems with NHST as it is typically used, and hence to proposals to limit the use of NHST techniques, to abandon these techniques and move to alternative statistical approaches, or even to ban the use of NHST entirely. These proposals are premature, because the observed problems with NHST all arise as a consequence of a contingent and in many cases incorrect choice: that of NHST testing against point-form nulls. We show that testing against distributional, rather than point-form, nulls is better motivated mathematically and experimentally, and that the use of distributional nulls addresses many problems with the standard point-form NHST approach. We also show that use of distributional nulls allows a form of null hypothesis testing that takes into account both the statistical significance of a given result and the probability of replication of that result in a new experiment. Rather than abandoning NHST, we should use the NHST approach in its more general form, with distributional rather than point-form nulls.
