Find Maximum value and ties based on different criteria

Question

For each combination of my variables simulation and iteration, I would like to

• find out whether group "a" had the highest value of rand1, as well as rand2,
• know whether group "a" tied with another group based on rand1, as well as rand2

Some sample df (with hard coded values for rand1 and rand2 for reproducibility:

df = crossing(simulation = 1:3,
              iteration = 1:3, 
              group =c("a","b","c")) %>%
mutate(rand1 = c(6,2,2,6,4,6, sample(6,21,replace=T)), # roundabout way to get the same head of df as in the example, forgot to use set.seed
       rand2 = c(4,1,2,5,6,1,sample(6,21,replace=T)))

which gives:

 simulation iteration group    rand1 rand2
          1         1 a            6     4
          1         1 b            2     1
          1         1 c            2     2
          1         2 a            6     5
          1         2 b            4     6
          1         2 c            6     1

This is what I want my output to look like: top.crit1 is 1 if group a is max, 0 if there is a tie. ties.crit1 lets me know if a was tied for max value with another group, same for top.crit2 and ties.crit2 [not added below to avoid cluttering] Desired output:

 simulation iteration group    rand1 rand2  top.crit1 ties.crit1 
          1         1 a            6     4  1         0
          1         1 b            2     1  1         0
          1         1 c            2     2  1         0
          1         2 a            6     5  0         1
          1         2 b            4     6  0         1
          1         2 c            6     1  0         1

This is my code so far for only determining the max value (but doesn't take into account ties), it's a bit tedious to determine the maximum value separately for rand1 and rand2.

  df.test = df %>%
  group_by(simulation, iteration) %>% 
  slice(which.max(rand1)) %>% 
  mutate(top.crit1 = if_else(group=="a",1,0)) %>% 
  select(-rand2, -rand1, -group) %>% 
  full_join(., df)

Answer 1

This would work if you arrange to have group a as first row of each group

df %>% group_by(simulation, iteration) %>% mutate(top.crit1 = rand1[1] > max(rand1[-1])) %>% mutate(ties.crit1 = rand1[1] == max(rand1[-1]))