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One method to identify rows that have the same repeated values in all groups can be achieved using the dplyr package in R. Here is an example:

1. Load the dplyr package:

library(dplyr)

1. Create a data frame with some example data:

df <- data.frame(group = c(1, 1, 2, 2),
                 value = c(2, 2, 3, 3))

This data frame has two columns, "group" and "value", and four rows. The first two rows have group value 1 and value 2, while the last two rows have group value 2 and value 3.

1. Use the group_by() and summarise() functions to group the data by the "value" column and count the number of unique groups that each value appears in:

df_summary <- df %>%
  group_by(value) %>%
  summarise(n_groups = n_distinct(group))

This creates a new data frame, where each row corresponds to a unique value in the original data frame and the "n_groups" column shows how many unique groups that value appears in.

1. Filter the data frame to only include rows where "n_groups" equals the total number of groups in the original data frame:

df_summary_filtered <- df_summary %>%
  filter(n_groups == n_distinct(df$group))

This creates a new data frame with only the rows that have the same repeated values in all groups.

In this example, the result would be:

  value n_groups
1     2        2
2     3        2

Both values 2 and 3 appear in both groups, so they satisfy the condition of having the same repeated values in all groups.