p -Values as QWERTY: Curating Evidence in the Computational Era
从计算统计学视角评论McShane等人对零假设显著性检验的批评，强调通过非参数、重抽样和贝叶斯方法进行估计与不确定性量化，并倡导研究者以多种方式估计关键量、可视化结果并记录分析路径。
McShane et al.'s (2024) wide-ranging critique of null hypothesis significance testing provides a number of specific suggestions for improved practice in empirical research. This commentary amplifies several of these from the perspective of computational statistics—particularly nonparametrics, resampling/bootstrapping, and Bayesian methods—applied to common research problems. Throughout, the author emphasizes estimation (as opposed to testing) and uncertainty quantification through a comprehensive process of “curating” a variety of graphical and tabular evidence. Specifically, researchers should be encouraged to estimate the quantities that matter, with as few assumptions as possible, in multiple ways, then try to visualize it all, documenting their pathway from data to results for others to follow.