Step 1: Identify the problem and the tool used

The problem is to determine if there are any significant differences between the medians of different groups, as indicated by the p-values from a Dunn test. The tool used is dunn.test in R.

Step 2: Understand how to get significance letters with dunn.test

To get significance letters directly from dunn.test without using pipes, you can use the cl argument and specify it as “none”. However, this will not provide any information.

Step 3: Determine a suitable alternative method

Instead of trying to modify the existing dunn.test command, we should consider how we can get significance letters in a more straightforward way. This involves creating a separate data frame that maps each group to its corresponding p-value.

Step 4: Implement an alternative approach using ggplot2 and dplyr

To accomplish this, we will use ggplot2 to create the boxplot and dplyr to manipulate the data for significance letters.

# Load necessary libraries
library(ggplot2)
library(dplyr)

# Assuming 'test_02' is your dataframe

# Create a new column that maps each group to its corresponding p-value
test_02$significance <- ifelse(test_02$p.value <= 0.05 / 2, "***", 
                              ifelse(test_02$p.value <= 0.05, "**", "."))

# Filter rows where significance is not "."
filtered_test_02 <- filter(test_02, significance != ".")

Step 5: Use ggplot2 to create the boxplot with significance letters

Then we can use ggplot2 to create a boxplot and add the significance letters.

ggplot(filtered_test_02, aes(x=Group, y=Mean)) + 
  geom_boxplot() + 
  labs(title="Boxplot of Means", x="Group", y="Mean") + 
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5))

The final answer is: $\boxed{None}$

Last modified on 2024-07-22