Meta-analysis, power analysis, and sensitivity analysis are widespread statistical techniques, which can be correctly performed only if variability statistics, such as standard deviation, are available; however, standard deviations are often missing in published articles. This work illustrates the functionality and the versatility of a newly developed Excel© tool for the standard deviation extraction from ANOVA and Multiple Comparison Test (MCT) results. The tool implements four methods, which can be alternatively applied according to the available statistics usually reported in ANOVA and/or MCT tables and graphs: 1) least significant difference (LSD), 2) significance level (p(F)), 3) letters for means separation assigned by MCT, 4) a range of significance level, indicated by "stars". The tool can be applied in one, two and three-way factorial experiments arranged in complete randomization, randomized block, split-plot or split-block. The performances of the different methods were tested in a case study about meta-analysis database preparation.

Meta 分析、功效分析和敏感性分析是广泛使用的统计技术，只有在可变性统计数据（例如标准差）可用时才能正确执行；然而，发表的文章中经常缺少标准偏差。这项工作说明了新开发的 Excel© 工具的功能和多功能性，用于从方差分析和多重比较测试 (MCT) 结果中提取标准偏差。该工具实现了四种方法，可以根据 ANOVA 和/或 MCT 表和图中通常报告的可用统计数据交替应用：1) 最小显着性差异 (LSD)，2) 显着性水平 (p(F))，3)由 MCT 指定的表示分离度的字母，4) 显着性水平范围，用“星星”表示。该工具可以应用在一个，以完全随机化、随机区组、裂区或裂区排列的二元和三元析因实验。在有关元分析数据库准备的案例研究中测试了不同方法的性能。