在R中多个子集上正确使用Anova和Anova

Question

我试图在一个数据帧的多个子集上运行一个双向的方差分析，而不必对数据进行实际的子集，因为这是有效的。

示例数据：

DF<-structure(list(Sample = c(666L, 676L, 686L, 667L, 677L, 687L, 
822L, 832L, 842L, 824L, 834L, 844L), Time = c(300L, 300L, 300L, 
300L, 300L, 300L, 400L, 400L, 400L, 400L, 400L, 400L), Ploidy = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("2n", 
"3n"), class = "factor"), Tissue = c("muscle", "muscle", "muscle", 
"liver", "liver", "liver", "intestine", "intestine", "intestine", 
"gill", "gill", "gill"), X.lipid = c(1.1, 0.8, 1.3, 3.7, 3.9, 
3.8, 5.2, 3.4, 6, 7.6, 10.4, 6.7), l.dec = c(0.011, 0.008, 0.013, 
0.037, 0.039, 0.038, 0.052, 0.034, 0.06, 0.076, 0.104, 0.067), 
l.arc = c(0.105074124512229, 0.0895624074394449, 0.114266036973812, 
0.193560218793138, 0.19879088899975, 0.196192082631721, 0.230059118691331, 
0.185452088760136, 0.247467063170448, 0.279298057669285, 
0.328359182374352, 0.261824790465914)), .Names = c("Sample", 
"Time", "Ploidy", "Tissue", "X.lipid", "l.dec", "l.arc"), row.names = c(1L, 
2L, 3L, 4L, 5L, 6L, 69L, 70L, 71L, 72L, 73L, 74L), class = "data.frame")

遇到类似的例子：Anova, for loop to apply function和ANOVA on multiple responses, by multiple groups NOT part of formula

我可以接近，但我不认为这是正确的，因为它使用的是aov，而不是anova。

x<- unique(DF$Tissue)

sapply(x, function(my) {
f <- as.formula(paste("l.dec~Time*Ploidy"))
aov(f, data=DF)
}, simplify=FALSE)

如果我将aov转换为anova，它将返回一条错误消息：

 Error in UseMethod("anova") : 
 no applicable method for 'anova' applied to an object of class "formula" 

有很长一段路要走，但这是正确的：

#Subset by each Tissue type (just one here for e.g.)
muscle<- subset (DF, Tissue == "muscle")
#Perform Anova
anova(lm(l.dec ~ Ploidy * Time, data = muscle))

然而，在主数据帧中，我有许多组织类型，希望避免执行这个子集。

我相信应用公式是接近的，但在最后阶段需要帮助。

Answer 1

基于@ use 20650和我上面的评论，我建议首先使用sapply和lm来生成模型列表，然后在列表上再次使用sapply来生成ANOVA表。这样你就可以得到模型的列表，这样你就可以得到系数，拟合值，残差等等。

x <- unique(DF$Tissue)

models <- sapply(x, function(my) {
  lm(l.dec ~ Time * Ploidy, data=DF, Tissue==my)
}, simplify=FALSE)

ANOVA.tables <- sapply(models, anova, simplify=FALSE)