pseudocode for knower level simulation

kl_sim.R

library(tidyverse)
library(assertthat)

shuffle_data <- function(d) {
  d$participant_id <- shuffle(d$participant_id)
  
  return(d)
}

get_knower_level <- function (q, r, technique = "perfect") {
 
 # perfect technique - your KL is the max q at which you get all correct
  if (technique == "perfect") {
    # fill in KL computation
  } else if (technique == "2/3") {
    # fill in KL computation    
  }
}

# test knowerlevel computation

# test 1: if you don't get anything right, your knower level is 0
assert_that(get_knower_level(c(1,2,3,4,5),c(0,0,0,0,0), technique = "perfect") == 0)

# test 2: if you get up to 3 right, your knower level is 3 (friendly test)
assert_that(get_knower_level(c(1,1,1,2,2,2,3,3,3,4,5),c(1,1,1,2,2,2,3,3,3,10,10)), technique = "perfect") == 3)

# make up unfriendly cases



knower_level_sim <- tibble(sim_num = 1:1000) |>
  mutate(data = shuffle_data(libertus_data)) |>
  unnest(cols = c(data)) |>
  group_by(sim_num, participant_id) |>
  summarise(knower_level_perfect = get_knower_level(quantity, response, 
                                                    technique = "perfect"),
            knower_level_23 = get_knower_level(quantity, response, 
                                            technique = "2/3")) |>
  group_by(sim_num, knower_level) |>
  count()