我的研究设计有三个相互作用的因素,我有16S微生物群落数据。我试图建立一个模型,在该模型中,我可以检验所有主效应(A,B,C)、双向交互作用(A:B,A:C,B:C)和三向交互作用(A:B:C)的效应,而无需指定因子的顺序(这是默认设置)。理想情况下,我会有一个类似的输出作为III型Anova。
使用边际检验(by = "margin"
)不起作用,因为当它这样写时,它只显示交互作用项的显著性(没有主效应)。
下面是一个只有两个因素的可重复的例子。
library(vegan)
data(dune)
data(dune.env)
adonis2(dune~Moisture*Manure,
data = dune.env,
permutations = 999,
method = "bray",
strata = dune.env$Management,
by = "margin")
产出:
Permutation test for adonis under reduced model
Marginal effects of terms
Blocks: strata
Permutation: free
Number of permutations: 999
adonis2(formula = dune ~ Moisture * Manure, data = dune.env, permutations = 999, method = "bray", by = "margin", strata = dune.env$Management)
Df SumOfSqs R2 F Pr(>F)
Moisture:Manure 4 0.4678 0.10881 0.9213 0.451
Residual 8 1.0154 0.23620
Total 19 4.2990 1.00000
当交互作用被写出时,
adonis2(dune~Moisture+Manure+Moisture:Manure,
data = dune.env,
permutations = 999,
method = "bray",
strata = dune.env$Management,
by = "margin")
产出:
Permutation test for adonis under reduced model
Marginal effects of terms
Blocks: strata
Permutation: free
Number of permutations: 999
adonis2(formula = dune ~ Moisture + Manure + Moisture:Manure, data = dune.env, permutations = 999, method = "bray", by = "margin", strata = dune.env$Management)
Df SumOfSqs R2 F Pr(>F)
Moisture:Manure 4 0.4678 0.10881 0.9213 0.424
Residual 8 1.0154 0.23620
Total 19 4.2990 1.00000
有没有一种合理的方法来做这件事,我可以同时测试主效应以及它们的相互作用?
谢谢你
1条答案
按热度按时间q43xntqr1#
边际检验之所以被称为边际检验,是因为它们只检验边际效应。如果有交互作用项,则这些交互作用是边际的,但其分量主效应不是边际的,并且不进行检验。在
adonis2
中没有“类型III”(有趣的名字)。没有人写过这些。