多组长格式rdplyr的事前后置假设检验

我有一个包含多个组的长格式数据集，我需要对每个组进行干预前后的假设检验.

我试图通过在组级别进行分组并对值和时间点执行测试来做到这一点，尽管出于某种原因，我得到的p值没有任何意义.他们都是一样的.请参见下面的示例:

# Load the required library
library(dplyr)

# Set seed for reproducibility
set.seed(123)

# Create a dataframe with unique ids, timepoints, foodgroups, and values
data <- data.frame(
  id = rep(1:10, each = 2),  # Increased sample size
  timepoint = rep(c("before", "after"), times = 100),
  group = rep(c("A", "B", "C", "D", "E"), each = 40),  # Adjusted for larger sample size
  value = rnorm(200)  # Generating random values for illustration
)

# Perform t-test for each foodgroup
result <- data %>%
  group_by(group) %>%
  summarise(
    p_value = wilcox.test(value ~ timepoint, data = ., paired = TRUE)$p.value
  )

# Print the results
print(result)

例如，如果我只 Select 如下所示的组，我就会得到一个唯一的、可能是准确的p值.

我想我对它们的分组方式有问题吧？

# Perform t-test for each foodgroup
result <- data %>%
  filter(group=='B') %>%
  summarise(
    p_value = wilcox.test(value ~ timepoint, data = ., paired = TRUE)$p.value
  )

# Print the results
print(result)

有没有人建议找出其中的问题或提出更好的方法来实现这个目标？