我目前正在寻找一种在 R 中执行邓恩测试的方法。在这样做的过程中,我遇到了多个实现了邓恩测试的功能。
library(dunn.test)
library(PMCMR)
dunn.test(x=mtcars[,"wt"], g= mtcars[,"cyl"])$P.adjusted
posthoc.kruskal.dunn.test(x=mtcars[,"wt"], g=mtcars[,"cyl"], p.adjust.method="bonferroni")
然而,结果完全不同。有人有使用dunn.test软件包的经验吗?我想使用邓斯测试作为Kruskal Wallis测试之后的事后测试。
他们使用一些不同的预设。您可以通过应用多重检验校正并对dunn.test
使用替代格式 p 值来获得相同的结果:
dunn.test(x=mtcars[,"wt"], g= mtcars[,"cyl"], method = 'bonferroni', altp = TRUE)$P.adjusted
Kruskal-Wallis rank sum test data: x and group Kruskal-Wallis chi-squared = 22.8067, df = 2, p-value = 0 Comparison of x by group (Bonferroni) Col Mean-| Row Mean | 4 6 ---------+---------------------- 6 | -1.836259 | 0.1990 | 8 | -4.755941 -2.221605 | 0.0000* 0.0789 alpha = 0.05 Reject Ho if p <= alpha
posthoc.kruskal.dunn.test(x=mtcars[,"wt"], g=mtcars[,"cyl"], p.adjust.method="bonferroni")
Pairwise comparisons using Dunn's-test for multiple comparisons of independent samples data: mtcars[, "wt"] and mtcars[, "cyl"] 4 6 6 0.199 - 8 5.9e-06 0.079 P value adjustment method: bonferroni