1 Biostatistics Department, MD Anderson Cancer Center, Houston, TX, USA.
2 Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Stat Methods Med Res. 2018 Nov;27(11):3411-3419. doi: 10.1177/0962280217702538. Epub 2017 Jun 20.
Altham (Altham PME. Exact Bayesian analysis of a 2 × 2 contingency table, and Fisher's "exact" significance test. J R Stat Soc B 1969; 31: 261-269) showed that a one-sided p-value from Fisher's exact test of independence in a 2 × 2 contingency table is equal to the posterior probability of negative association in the 2 × 2 contingency table under a Bayesian analysis using an improper prior. We derive an extension of Fisher's exact test p-value in the presence of missing data, assuming the missing data mechanism is ignorable (i.e., missing at random or completely at random). Further, we propose Bayesian p-values for a test of independence in a 2 × 2 contingency table with missing data using alternative priors; we also present results from a simulation study exploring the Type I error rate and power of the proposed exact test p-values. An example, using data on the association between blood pressure and a cardiac enzyme, is presented to illustrate the methods.
阿尔瑟姆(Altham PME。2×2 列联表的确切贝叶斯分析和 Fisher 的“确切”显著性检验。J R Stat Soc B 1969;31: 261-269)表明,在 2×2 列联表中使用不适当先验进行贝叶斯分析时,Fisher 独立性检验的单侧 p 值等于 2×2 列联表中负关联的后验概率。我们推导出了在存在缺失数据的情况下 Fisher 精确检验 p 值的扩展,假设缺失数据机制是可忽略的(即随机缺失或完全随机缺失)。此外,我们提出了使用替代先验的 2×2 列联表中缺失数据独立性检验的贝叶斯 p 值;我们还提供了一项模拟研究的结果,该研究探讨了所提出的精确检验 p 值的Ⅰ类错误率和功效。使用血压和心脏酶之间关联的数据,提供了一个示例来说明这些方法。