是否有用于多组拟合优度卡方检验的 R 函数？

Question

S.giganteus <- matrix(c(0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 1, 6, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 1, 7, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 6, 6, 0, 0, 0, 0, 0, 0, 2, 3, 0, 0, 0, 0, 0, 0, 1, 4, 0, 0, 0, 0, 0, 0, 4, 2, 0, 0, 0, 0, 0, 1, 4, 1, 0, 0), ncol = 7, byrow = T)
colnames (S.giganteus) <- c("s1", "s2", "s3", "s4", "s5", "s6", "s7")
rownames (S.giganteus) <- c("feb", "mar", "apr", "may", "jun", "jul", "aug", "sep", "oct", "nov", "dec", "jan")
S.giganteus <- as.table(S.giganteus)

P.melanotus <- matrix(c(0, 0, 0, 0, 4, 1, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 4, 7, 6, 0, 0, 0, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 7, 2, 0, 0, 0, 0, 0, 1, 2, 1, 0, 0, 0, 0, 4, 1, 1, 0, 0, 0, 0, 0, 3, 5, 0, 0, 0, 0, 0, 3, 8, 1, 0, 0, 0, 0, 0, 3, 1, 0, 0, 0))
colnames (P.melanotus) <- c("s1", "s2", "s3", "s4", "s5", "s6", "s7")
rownames (P.melanotus) <- c("feb", "mar", "apr", "may", "jun", "jul", "aug", "sep", "oct", "nov", "dec", "jan")
P.melanotus <- as.table(P.melanotus)

我不知道这是否可能，但我想做多项拟合优度卡方检验。换句话说，我想将一个月内不同阶段的S.giganteus个体的比例与P.melanotus的实际个体数量进行比较。 由于抽样工作的差异以及因此组大小的不平等，我无法进行正常的卡方检验。 我希望避免每月单独进行测试，以减少出现 I 类错误的可能性。 我不知道从哪里开始，也不知道这是否可能，因为我在网上找不到任何东西。当然，我也愿意接受其他选择。

Answer 1

我不确定此内容的目标是什么，但这就是我发现的。我确实想说，我不确定你所说的不均匀的组大小是什么意思，因为两者都是 12 x 7。

S.giganteus <- matrix(c(0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 1, 6, 0, 0, 0, 
                        0, 0, 2, 2, 0, 0, 0, 0, 0, 1, 7, 0, 0, 0, 0, 0,
                        0, 6, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 6, 
                        6, 0, 0, 0, 0, 0, 0, 2, 3, 0, 0, 0, 0, 0, 0, 1, 
                        4, 0, 0, 0, 0, 0, 0, 4, 2, 0, 0, 0, 0, 0, 1, 4, 
                         1, 0, 0), ncol = 7, byrow = T)
colnames (S.giganteus) <- c("s1", "s2", "s3", "s4", "s5", "s6", "s7")
rownames (S.giganteus) <- c("feb", "mar", "apr", "may", "jun", "JUL", 
                            "aug", "sep", "oct", "nov", "dec", "jan")
(S.giganteus <- as.table(S.giganteus))

P.melanotus <- matrix(c(0, 0, 0, 0, 4, 1, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 
                        0, 0, 0, 4, 7, 6, 0, 0, 0, 0, 0, 0, 8, 0, 0, 0, 
                        0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 7, 2, 0, 0, 0, 0, 
                        0, 1, 2, 1, 0, 0, 0, 0, 4, 1, 1, 0, 0, 0, 0, 0, 
                        3, 5, 0, 0, 0, 0, 0, 3, 8, 1, 0, 0, 0, 0, 0, 3, 
                        1, 0, 0, 0), ncol = 7, byrow = T)
colnames (P.melanotus) <- c("s1", "s2", "s3", "s4", "s5", "s6", "s7")
rownames (P.melanotus) <- c("feb", "mar", "apr", "may", "jun", "JUL", 
                            "aug", "sep", "oct", "nov", "dec", "jan")
(P.melanotus <- as.table(P.melanotus))

然后我应用了卡方-

chisq.test(S.giganteus, P.giganteus)
# 
#   Pearson's Chi-squared test
# 
# data:  S.giganteus
# X-squared = 212.12, df = 66, p-value < 2.2e-16
#  

由于警告 –

警告消息：
在 chisq.test(S.giganteus, P.giganteus) 中：卡方近似可能不正确

我使用了 MC 模拟：

chisq.test(S.giganteus, P.giganteus, simulate.p.value = T)
# 
#   Pearson's Chi-squared test with simulated p-value (based on 2000
#   replicates)
# 
# data:  S.giganteus
# X-squared = 212.12, df = NA, p-value = 0.0004998
#