Chisq和Fishers临时测试

问题描述

我正在尝试对chisq和Fisher精确测试进行事后测试。我正在使用的数据帧是2x3。我运行了一个chisq检验，该检验产生了显着的p值，但是当我检查期望值时，该值小于5，因此我运行了Fisher精确检验，该检验也返回了小于0.05的p值。我现在尝试测试哪些交互很重要，因此我尝试运行chisq.posthoc.test，pairwise.fisher和fisher.multcomp测试，但是返回的值返回的很奇怪，我不确定如果我运行的代码错误，或者下一步该怎么做。我对R还是比较陌生，所以有点卡住了。

如果有人可以帮助我解决正在发生的事情以及下一步我该做什么，我将不胜感激。

tally_spawnsl<-
  data%>%
  group_by(Spawn_Type,spawn_false,Lunar_Phase_Boxed) %>%
  filter(spawn_false=="TRUE")%>%
  tally()

print.data.frame(tally_spawnsl)

  Spawn_Type spawn_false Lunar_Phase_Boxed   n
1      Group        TRUE              Full 372
2      Group        TRUE              Half 134
3      Group        TRUE               New 348
4       Pair        TRUE              Full  20
5       Pair        TRUE              Half   3
6       Pair        TRUE               New   4

spawntypesl<- data.frame(
  expand.grid(lunarphase=c("Full","Half","New"),type=c("Group","Pair")),count=c(372,134,348,20,3,4))

spawntypesl

  lunarphase  type count
1       Full Group   372
2       Half Group   134
3        New Group   348
4       Full  Pair    20
5       Half  Pair     3
6        New  Pair     4

tablel<-xtabs(count~lunarphase+type,data=spawntypesl)
tablel

          type
lunarphase Group Pair
      Full   372   20
      Half   134    3
      New    348    4

summary(tablel)
Call: xtabs(formula = count ~ lunarphase + type,data = spawntypesl)
Number of cases in table: 881 
Number of factors: 2 
Test for independence of all factors:
    Chisq = 10.236,df = 2,p-value = 0.005988
    Chi-squared approximation may be incorrect

chisq.test(tablel,simulate.p.value=TRUE)

    Pearson's Chi-squared test with simulated p-value (based on 2000 replicates)

data:  tablel
X-squared = 10.236,df = NA,p-value = 0.002999

chisq.test(tablel)$expected
          type
lunarphase    Group      Pair
      Full 379.9864 12.013621
      Half 132.8014  4.198638
      New  341.2123 10.787741

library(devtools)
devtools::install_github("ebbertd/chisq.posthoc.test")
chisq.posthoc.test::chisq.posthoc.test(tablel,method = "bonferroni")```

  Dimension     Value             Group               Pair
1      Full Residuals -3.14127171999929   3.14127171999929
2      Full  p values           0.0101*            0.0101*
3      Half Residuals 0.646538369476683 -0.646538369476691
4      Half  p values                 1                  1
5       New Residuals  2.70881379836813  -2.70881379836813
6       New  p values           0.0405*            0.0405*

####Fisher Test for lunar phase and spawn type####

fishertestl<-fisher.test(tablel)
fishertestl
    Fisher's Exact Test for Count Data

data:  tablel
p-value = 0.005426
alternative hypothesis: two.sided

fishertestl$p.value
[1] 0.005426258

fisher.multcomp(tablel,p.method = "none")

        Pairwise comparisons using Fisher's exact test for count data

data:  tablel

         Full   Half
Half 0.222207      -
New  0.002811 0.4062

P value adjustment method: none

> chisq.posthoc.test::chisq.posthoc.test(tablel,method = "bonferroni")
  Dimension     Value             Group               Pair
1      Full Residuals -3.14127171999929   3.14127171999929
2      Full  p values           0.0101*            0.0101*
3      Half Residuals 0.646538369476683 -0.646538369476691
4      Half  p values                 1                  1
5       New Residuals  2.70881379836813  -2.70881379836813
6       New  p values           0.0405*            0.0405*
Warning message:
In chisq.test(x,...) : Chi-squared approximation may be incorrect
> fisher.multcomp(tablel,p.method = "bonferroni")

        Pairwise comparisons using Fisher's exact test for count data

data:  tablel

         Full Half
Half 0.666620    -
New  0.008432    1

P value adjustment method: bonferroni
> chisq.posthoc.test::chisq.posthoc.test(tablel,method = "none")
  Dimension     Value             Group               Pair
1      Full Residuals -3.14127171999929   3.14127171999929
2      Full  p values           0.0017*            0.0017*
3      Half Residuals 0.646538369476683 -0.646538369476691
4      Half  p values            0.5179             0.5179
5       New Residuals  2.70881379836813  -2.70881379836813
6       New  p values           0.0068*            0.0068*
Warning message:
In chisq.test(x,p.method = "none")

        Pairwise comparisons using Fisher's exact test for count data

data:  tablel

         Full   Half
Half 0.222207      -
New  0.002811 0.4062

P value adjustment method: none

解决方法

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