我试图获得与用函数pairwise.wilcox.test()生成的p值相关的紧凑字母。我使用了函数multcompLetters(),它工作得很好,但我希望字母被排序,以便最高的平均值得到字母“a”。在下面的例子中,当使用函数multcompLetters()来排序字母时,我收到了警告:“tapply(data[,fm1],data[,fm2],function(x)do.call(mean,:arguments must have same length)中出错”。
有什么我不明白的功能的用法吗?
多谢了
**正在添加 Dataframe **
As15 <- structure(list(Community = c("Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat", "Arviat",
"Arviat", "Arviat", "Arviat", "Nain", "Nain", "Nain", "Nain",
"Nain", "Nain", "Nain", "Nain", "Nain", "Nain", "Nain", "Nain",
"Nain", "Nain", "Nain", "Nain", "Nain", "Nain", "Nain", "Nain",
"Nain", "Nain", "Nain", "Nain", "Nain", "Nain", "Nain", "Nain",
"Nain", "Nain", "Nain", "Nain", "Nain", "Nain", "Nain", "Nain",
"Nain", "Nain", "Nain", "Nain", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "Resolute", "Resolute", "Resolute",
"Resolute", "Resolute", "Resolute", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour", "SachsHarbour",
"SachsHarbour", "SachsHarbour", "SachsHarbour"), ArsenicD = c(0.0254,
0.121, 0.0726, 0.021, 0.0782, 0.0538, 0.1078, 0.0454, 0.0368,
0.0618, 0.037, 0.0754, 0.1394, 0.0784, 0.218, 0.1482, 0.0778,
0.0592, 0.0314, 0.0232, 0.0548, 0.0662, 0.0604, 0.0252, 0.0502,
0.0768, 0.036, 0.054, 0.0404, 0.0642, 0.0384, 0.0504, 0.0616,
0.068, 0.0678, 0.06, 0.0526, 0.0454, 0.0574, 0.0462, 0.0558,
0.0506, 0.0764, 0.0466, 0.0518, 0.0544, 0.0362, 0.0472, 0.0374,
0.0564, 0.0512, 0.0442, 0.0526, 0.05, 0.047, 0.0456, 0.073, 0.0798,
0.0544, 0.072, 0.0392, 0.0658, 0.1662, 0.036, 0.0562, 0.0584,
0.0416, 0.037, 0.046, 0.0334, 0.0384, 0.0654, 0.0528, 0.0274,
0.0368, 0.0634, 0.0308, 0.0702, 0.0502, 0.058, 0.037, 0.0456,
0.0404, 0.0516, 0.051, 0.0484, 0.054, 0.0344, 0.064, 0.0548,
0.032, 0.0532, 0.0562, 0.0464, 0.0334, 0.068, 0.0422, 0.298,
0.0344, 0.0338, 0.0508, 0.0356, 0.0446, 0.0484, 0.0408, 0.0148,
0.0374, 0.0244, 0.0644, 0.0574, 0.028, 0.0462, 0.067, 0.0472,
0.053, 0.0418, 0.0324, 0.054, 0.04, 0.0506, 0.0592, 0.0356, 0.049,
0.054, 0.296, 0.276, 0.226, 0.0834, 0.452, 0.306, 0.218, 0.33,
0.208, 0.1628, 0.426, 0.376, 0.0894, 0.438, 0.334, 0.212, 0.1606,
0.082, 0.1178, 0.1128, 0.142, 0.103, 0.0862, 0.1104, 0.0746,
0.0954, 0.202, 0.1362, 0.24, 0.21, 0.172, 0.278, 0.1354, 0.274,
0.228, 0.0854, 0.0924, 0.0992, 0.0648, 0.0548, 0.0768, 0.0996,
0.1008, 0.063, 0.0372, 0.1582, 0.228, 0.1514, 0.218, 0.1612,
0.1608, 0.1652, 0.1474, 0.1904, 0.0396, 0.1396, 0.0816, 0.1132,
0.0968, 1.258, 0.326, 0.236, 0.0854, 0.256, 0.1258, 0.1324, 0.1716,
0.1642, 0.22, 0.0836, 0.18, 0.274, 0.1918, 0.171, 0.356, 0.298,
0.1084, 0.1436, 0.238, 0.348, 0.1496, 0.342, 0.434, 0.146, 0.174,
0.288, 0.396, 0.1834, 0.64, 0.342, 0.686, 0.43, 0.1808, 0.454,
0.482, 0.352, 0.476, 0.422, 0.286, 0.81, 0.656, 0.564, 0.119,
0.296, 0.1778, 0.512, 0.278, 0.22, 0.208, 0.1474, 0.55, 0.1526,
0.1858, 0.128, 0.224, 0.1752, 0.0724, 0.1302, 0.1724, 0.1354,
0.104, 0.1132, 0.292, 0.238, 0.348, 0.1626, 0.312, 0.238, 0.236,
0.1276, 0.1228, 0.0978, 0.376, 0.1968, 0.1164, 0.448, 0.2, 0.1322,
0.117)), row.names = c(NA, -263L), class = c("tbl_df", "tbl",
"data.frame"))
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Wilcoxon检验
As15Wilcox <- suppressWarnings(pairwise.wilcox.test(As15$ArsenicD, As15$Community, p.adjust.method = "BH"))
As15pvals <- c(na.omit(setNames(c(As15Wilcox$p.value),
do.call("paste", c(as.list(expand.grid(rownames(As15Wilcox$p.value),
colnames(As15Wilcox$p.value))), sep = "-")))))
型
获取信件
multcompLetters2(ArsenicD ~ Community, As15pvals, As15)
型
我用length()验证了,ArsenicD和Community具有相同的长度。
1条答案
按热度按时间f2uvfpb91#
不清楚为什么您认为可以将
pairwise.wilcox.test
的输出传递给multcompLetters2
的第二个参数(参数x
)。根据文档:x
...而
wilcox1
是类"pairwise.htest"
的对象。然而,它确实 * 包含 * 比较的p值矩阵,我们可以将其转换为上述格式之一。让我们用一个与您的数据集类似的数据集进行演示。
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使用你的代码,我们得到一个错误:
型
让我们从
wilcox1
对象中获取p值,并转换为具有正确对名称的命名向量:型
现在我们可以做到:
型
使用数据
显然,我们没有您的数据,所以这里是一个可复制的示例,具有与我在此示例中使用的相同的名称和基本结构:
型
创建于2023-07-26带有reprex v2.0.2