Performing Wilcoxon test with multiple test groups

Question

I want to run Wilcoxon test to compare 3 test groups (B, C and D) against the control group (A)

The data are organized in the following format:

Group   CustomerID  Value
A           23483   61
A           23484   54
A           23485   57
A           23486   59
A           23487   69
A           23488   69
B           23489   57
B           23490   53
B           23491   68
B           23492   59
B           23493   57
C           23494   58
C           23495   70
C           23496   69
C           23497   62
C           23498   53
D           23499   65
D           23500   62
D           23501   60
D           23502   62
D           23503   63
D           23504   68

So far I've written the code below

#Seperate Control Data
DataControl<- Data%>%
                select(Group,Value)%>%
                filter(Group =="A")

#Filter data
Data%>%
  filter(Group!="A")%>%
  select(Group,Value)%>%
  group_by(Group)
  summarise(p_value = wilcox.test(DataControl$Value,exact =FALSE)$p.value)

but I am getting the following errors

Error in summarise_(.data, .dots = compat_as_lazy_dots(...)) : 
  argument ".data" is missing, with no default

The desired output shall be

Group P-value
B     0.04
C     0.10
D     0.01

Answer 1

There's a built-in pairwise function; I'd start there. Then just tidy it up and pick the pieces you need.

Note that my code (and yours too) doesn't correct for multiple comparisons. You should think about if that's appropriate here.

foo <- pairwise.wilcox.test(Data$Value, Data$Group, p.adjust.method="none")
foo

## Pairwise comparisons using Wilcoxon rank sum test 
## data:  Data$Value and Data$Group 

##   A     B     C    
## B 0.355 -     -    
## C 0.782 0.344 -    
## D 0.470 0.098 0.927
##
## P value adjustment method: none 

library(tidyverse)
broom::tidy(foo) %>% filter(group2=="A")
## # A tibble: 3 x 3
##   group1 group2 p.value
##   <chr>  <chr>    <dbl>
## 1 B      A        0.355
## 2 C      A        0.782
## 3 D      A        0.470