Question

我试图在数据中进行有效的三向交互以获得最低的显着差异，但是我对以这种方式使用R不太熟悉。

这是我正在使用的数据集的头（不确定如何共享整个事情）：

> dput(head(data)) 
structure(list(ï..Sample = c(1012L, 1026L, 1033L, 1042L, 1053L, 
1061L), Collection = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0 Months", 
"4 Months", "8 Months"), class = "factor"), Irrigation = structure(c(4L, 
5L, 4L, 5L, 5L, 2L), .Label = c("100%", "125%", "50%", "75%", 
"75%50%"), class = "factor"), Variety = structure(c(1L, 1L, 1L, 
1L, 1L, 1L), .Label = c("Hodag", "Lamoka", "Snowden"), class = "factor"), 
    Suc = c(0.4717, 0.6833, 0.6467, 0.805, 0.455, 0.6217), Gluc = c(0.04, 
    0.087, 0.06, 0.07, 0.055, 0.025), L = c(57.59, 65.65, 66.58, 
    66.86, 68.52, 54.93), a = c(6.85, 2.84, 2.77, 1.86, 0.99, 
    7.59), b = c(27.6, 27.19, 27.54, 26.99, 25.62, 26.11), NoDefect = c(100, 
    100, 100, 100, 100, 100), Defect = c(0L, 0L, 0L, 0L, 0L, 
    0L)), row.names = c(NA, 6L), class = "data.frame")

当我进行方差分析时，我发现这里存在显着的三向交互作用

#Glucose
lmGluc <- aov(Gluc~Collection*Irrigation*Variety, data=data)
summary(lmGluc)

非常感谢获得有关该交互的LSD的任何帮助。谢谢！

如何为三向交互找到LSD？

0 个答案: