Shafer (2021) offers a betting perspective on statistical testing which may be useful for foundational debates, given that disputes over such testing continue to be intense. To be helpful for researchers, however, this perspective will need more elaboration using real examples in which (a) the betting score has a justification and interpretation in terms of study goals that distinguishes it from the uncountable mathematical possibilities, and (b) the assumptions in the sampling model are uncertain. On justification, Shafer says 'No one has made a convincing case for any particular choice' of a score derived from a P-value and then states that 'the choice is fundamentally arbitrary'. Yet some (but not most) scores can be motivated by study goals (e.g., information measurement; decision making). The one I have seen repeatedly in information statistics and data mining is the surprisal, logworth or S-value s = -log(p), where the log base determines the scale. The present comment explains the rationale for this choice.
翻译:Shafer(2021年)为统计测试提供了一种可能有益于基础辩论的赌注视角,因为关于此类测试的争议仍然十分激烈。但是,为了对研究人员有所帮助,这一视角需要用真实的例子进行更多的阐述,例如:(a) 赌注得分在研究目标方面有合理的理由和解释,将其与无法计算的数学可能性区分开来,以及(b) 抽样模型中的假设不确定。关于理由,Shafer说,“没有人对从P值中得分的任何特定选择提出令人信服的理由”,然后说“选择基本上是任意的”。然而,有些(但不是大多数)得分可以由研究目标(例如信息计量;决策)驱动。我在信息统计和数据挖掘中反复看到的一个得分是日志、logworth或S-values = -log(p), 日志基在其中决定比额表。本评论解释了这一选择的理由。