tests/testthat/test_select_boin_mtd.R

In escalation: Modular Approach to Dose Finding Clinical Trials

test_that('select_boin_mtd works like it should.', {

  # Example from p.15 of Yan et al. (2019):
  n <- c(3, 3, 15, 9, 0)
  y <- c(0, 0, 4, 4, 0)
  x <- BOIN::select.mtd(target = 0.3, ntox = y, npts = n)

  model1 <- get_boin(num_doses = 5, target = 0.3) %>%
    stop_at_n(n = 30) %>%
    select_boin_mtd()
  outcomes <- '1NNN 2NNN 3NNN 3NNN 3NNN 3NNT 3TTT 4NNN 4NNT 4TTT'
  expect_equal(model1 %>% fit(outcomes) %>% recommended_dose(), x$MTD)
  # The trouble is, get_boin alone would also advocate the same dose:
  model2 <- get_boin(num_doses = 5, target = 0.3) %>%
    stop_at_n(n = 30)
  expect_equal(model2 %>% fit(outcomes) %>% recommended_dose(), x$MTD)


  # So, to observe that select_boin_mtd is having the desired effect, contrive
  # a scenario where we know it will diverge from ordinary BOIN, which will only
  # recommend doses with a single dose of the current dose:
  model3 <- get_boin(num_doses = 5, target = 0.3) %>%
    stop_at_n(n = 30) %>%
    select_boin_mtd(when = 'always')
  outcomes <- '2NNT 5TTT'
  expect_lt(model3 %>% fit(outcomes) %>% recommended_dose(),
            model2 %>% fit(outcomes) %>% recommended_dose())
  n <- c(0, 3, 0, 0, 3)
  y <- c(0, 1, 0, 0, 3)
  x <- BOIN::select.mtd(target = 0.3, ntox = y, npts = n)
  expect_equal(model3 %>% fit(outcomes) %>% recommended_dose(), x$MTD)

  # At this low sample size, model 2 is not different to a model where
  # select_boin_mtd only intervenes finally:
  model4 <- get_boin(num_doses = 5, target = 0.3) %>%
    stop_at_n(n = 30) %>%
    select_boin_mtd(when = 'finally')
  expect_equal(model2 %>% fit(outcomes) %>% recommended_dose(),
               model4 %>% fit(outcomes) %>% recommended_dose())
})

test_that('select_boin_mtd(when=finally) supports correct interface.', {

  num_doses <- 5
  target <- 0.3

  model_fitter <- get_boin(num_doses = num_doses, target = target) %>%
    select_boin_mtd(when = 'finally')

  # Example 1, using outcome string
  x <- fit(model_fitter, '1NNN 2NTT')

  expect_equal(tox_target(x), 0.3)
  expect_true(is.numeric(tox_target(x)))

  expect_equal(num_patients(x), 6)
  expect_true(is.integer(num_patients(x)))

  expect_equal(cohort(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(cohort(x)))
  expect_equal(length(cohort(x)), num_patients(x))

  expect_equal(doses_given(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(doses_given(x)))
  expect_equal(length(doses_given(x)), num_patients(x))

  expect_equal(tox(x), c(0,0,0, 0,1,1))
  expect_true(is.integer(tox(x)))
  expect_equal(length(tox(x)), num_patients(x))

  expect_true(all((model_frame(x) - data.frame(patient = c(1,2,3,4,5,6),
                                               cohort = c(1,1,1,2,2,2),
                                               dose = c(1,1,1,2,2,2),
                                               tox = c(0,0,0,0,1,1))) == 0))
  expect_equal(nrow(model_frame(x)), num_patients(x))

  expect_equal(num_doses(x), 5)
  expect_true(is.integer(num_doses(x)))

  expect_equal(dose_indices(x), 1:5)
  expect_true(is.integer(dose_indices(x)))
  expect_equal(length(dose_indices(x)), num_doses(x))

  expect_equal(recommended_dose(x), 1)
  expect_true(is.integer(recommended_dose(x)))
  expect_equal(length(recommended_dose(x)), 1)

  expect_equal(continue(x), TRUE)
  expect_true(is.logical(continue(x)))

  expect_equal(n_at_dose(x), c(3,3,0,0,0))
  expect_true(is.integer(n_at_dose(x)))
  expect_equal(length(n_at_dose(x)), num_doses(x))

  expect_equal(n_at_dose(x, dose = 0), 0)
  expect_true(is.integer(n_at_dose(x, dose = 0)))
  expect_equal(length(n_at_dose(x, dose = 0)), 1)

  expect_equal(n_at_dose(x, dose = 1), 3)
  expect_true(is.integer(n_at_dose(x, dose = 1)))
  expect_equal(length(n_at_dose(x, dose = 1)), 1)

  expect_equal(n_at_dose(x, dose = 'recommended'), 3)
  expect_true(is.integer(n_at_dose(x, dose = 'recommended')))
  expect_equal(length(n_at_dose(x, dose = 'recommended')), 1)

  expect_equal(n_at_recommended_dose(x), 3)
  expect_true(is.integer(n_at_recommended_dose(x)))
  expect_equal(length(n_at_recommended_dose(x)), 1)

  expect_equal(is_randomising(x), FALSE)
  expect_true(is.logical(is_randomising(x)))
  expect_equal(length(is_randomising(x)), 1)

  expect_equal(unname(prob_administer(x)), c(0.5,0.5,0,0,0))
  expect_true(is.numeric(prob_administer(x)))
  expect_equal(length(prob_administer(x)), num_doses(x))

  expect_equal(tox_at_dose(x), c(0,2,0,0,0))
  expect_true(is.integer(tox_at_dose(x)))
  expect_equal(length(tox_at_dose(x)), num_doses(x))

  expect_true(is.numeric(empiric_tox_rate(x)))
  expect_equal(length(empiric_tox_rate(x)), num_doses(x))

  expect_true(is.numeric(mean_prob_tox(x)))
  expect_equal(length(mean_prob_tox(x)), num_doses(x))

  expect_true(is.numeric(median_prob_tox(x)))
  expect_equal(length(median_prob_tox(x)), num_doses(x))

  expect_true(is.logical(dose_admissible(x)))
  expect_equal(length(dose_admissible(x)), num_doses(x))

  expect_true(is.numeric(prob_tox_quantile(x, p = 0.9)))
  expect_equal(length(prob_tox_quantile(x, p = 0.9)), num_doses(x))

  expect_true(is.numeric(prob_tox_exceeds(x, 0.5)))
  expect_equal(length(prob_tox_exceeds(x, 0.5)), num_doses(x))

  expect_true(is.logical(supports_sampling(x)))

  expect_error(prob_tox_samples(x))
  expect_error(prob_tox_samples(x, tall = TRUE))

  # Expect summary to not error. This is how that is tested, apparently:
  expect_error(summary(x), NA)
  expect_output(print(x))
  expect_true(tibble::is_tibble(as_tibble(x)))
  expect_true(nrow(as_tibble(x)) >= num_doses(x))


  # Example 2, using trivial outcome string
  x <- fit(model_fitter, '')

  expect_equal(tox_target(x), 0.3)
  expect_true(is.numeric(tox_target(x)))

  expect_equal(num_patients(x), 0)
  expect_true(is.integer(num_patients(x)))

  expect_equal(cohort(x), integer(0))
  expect_true(is.integer(cohort(x)))
  expect_equal(length(cohort(x)), num_patients(x))

  expect_equal(doses_given(x), integer(0))
  expect_true(is.integer(doses_given(x)))
  expect_equal(length(doses_given(x)), num_patients(x))

  expect_equal(tox(x), integer(0))
  expect_true(is.integer(tox(x)))
  expect_equal(length(tox(x)), num_patients(x))

  expect_equal(num_tox(x), 0)
  expect_true(is.integer(num_tox(x)))

  expect_equal(dose_indices(x), 1:5)
  expect_true(is.integer(dose_indices(x)))
  expect_equal(length(dose_indices(x)), num_doses(x))

  mf <- model_frame(x)
  expect_equal(nrow(mf), 0)
  expect_equal(ncol(mf), 4)

  expect_equal(num_doses(x), 5)
  expect_true(is.integer(num_doses(x)))

  expect_equal(recommended_dose(x), 1)
  expect_true(is.integer(recommended_dose(x)))
  expect_equal(length(recommended_dose(x)), 1)

  expect_equal(continue(x), TRUE)
  expect_true(is.logical(continue(x)))

  expect_equal(n_at_dose(x), c(0,0,0,0,0))
  expect_true(is.integer(n_at_dose(x)))
  expect_equal(length(n_at_dose(x)), num_doses(x))

  expect_equal(n_at_dose(x, dose = 0), 0)
  expect_true(is.integer(n_at_dose(x, dose = 0)))
  expect_equal(length(n_at_dose(x, dose = 0)), 1)

  expect_equal(n_at_dose(x, dose = 1), 0)
  expect_true(is.integer(n_at_dose(x, dose = 1)))
  expect_equal(length(n_at_dose(x, dose = 1)), 1)

  expect_equal(n_at_dose(x, dose = 'recommended'), 0)
  expect_true(is.integer(n_at_dose(x, dose = 'recommended')))
  expect_equal(length(n_at_dose(x, dose = 'recommended')), 1)

  expect_equal(n_at_recommended_dose(x), 0)
  expect_true(is.integer(n_at_recommended_dose(x)))
  expect_equal(length(n_at_recommended_dose(x)), 1)

  expect_equal(is_randomising(x), FALSE)
  expect_true(is.logical(is_randomising(x)))
  expect_equal(length(is_randomising(x)), 1)

  expect_true(is.numeric(prob_administer(x)))
  expect_equal(length(prob_administer(x)), num_doses(x))

  expect_equal(tox_at_dose(x), c(0,0,0,0,0))
  expect_true(is.integer(tox_at_dose(x)))
  expect_equal(length(tox_at_dose(x)), num_doses(x))

  expect_true(is.numeric(empiric_tox_rate(x)))
  expect_equal(length(empiric_tox_rate(x)), num_doses(x))

  expect_true(is.numeric(mean_prob_tox(x)))
  expect_equal(length(mean_prob_tox(x)), num_doses(x))

  expect_true(is.numeric(median_prob_tox(x)))
  expect_equal(length(median_prob_tox(x)), num_doses(x))

  expect_true(is.logical(dose_admissible(x)))
  expect_equal(length(dose_admissible(x)), num_doses(x))

  expect_true(is.numeric(prob_tox_quantile(x, p = 0.9)))
  expect_equal(length(prob_tox_quantile(x, p = 0.9)), num_doses(x))

  expect_true(is.numeric(prob_tox_exceeds(x, 0.5)))
  expect_equal(length(prob_tox_exceeds(x, 0.5)), num_doses(x))

  expect_true(is.logical(supports_sampling(x)))

  expect_error(prob_tox_samples(x))
  expect_error(prob_tox_samples(x, tall = TRUE))

  # Expect summary to not error. This is how that is tested, apparently:
  expect_error(summary(x), NA)
  expect_output(print(x))
  expect_true(tibble::is_tibble(as_tibble(x)))
  expect_true(nrow(as_tibble(x)) >= num_doses(x))


  # Example 3, using tibble
  outcomes <- tibble(
    cohort = c(1,1,1, 2,2,2),
    dose = c(1,1,1, 2,2,2),
    tox = c(0,0, 0,0, 1,1)
  )
  x <- fit(model_fitter, outcomes)

  expect_equal(tox_target(x), 0.3)
  expect_true(is.numeric(tox_target(x)))

  expect_equal(num_patients(x), 6)
  expect_true(is.integer(num_patients(x)))

  expect_equal(cohort(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(cohort(x)))
  expect_equal(length(cohort(x)), num_patients(x))

  expect_equal(doses_given(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(doses_given(x)))
  expect_equal(length(doses_given(x)), num_patients(x))

  expect_equal(tox(x), c(0,0,0, 0,1,1))
  expect_true(is.integer(tox(x)))
  expect_equal(length(tox(x)), num_patients(x))

  expect_true(all((model_frame(x) - data.frame(patient = c(1,2,3,4,5,6),
                                               cohort = c(1,1,1,2,2,2),
                                               dose = c(1,1,1,2,2,2),
                                               tox = c(0,0,0,0,1,1))) == 0))
  expect_equal(nrow(model_frame(x)), num_patients(x))

  expect_equal(num_doses(x), 5)
  expect_true(is.integer(num_doses(x)))

  expect_equal(dose_indices(x), 1:5)
  expect_true(is.integer(dose_indices(x)))
  expect_equal(length(dose_indices(x)), num_doses(x))

  expect_equal(recommended_dose(x), 1)
  expect_true(is.integer(recommended_dose(x)))
  expect_equal(length(recommended_dose(x)), 1)

  expect_equal(continue(x), TRUE)
  expect_true(is.logical(continue(x)))

  expect_equal(n_at_dose(x), c(3,3,0,0,0))
  expect_true(is.integer(n_at_dose(x)))
  expect_equal(length(n_at_dose(x)), num_doses(x))

  expect_equal(n_at_dose(x, dose = 0), 0)
  expect_true(is.integer(n_at_dose(x, dose = 0)))
  expect_equal(length(n_at_dose(x, dose = 0)), 1)

  expect_equal(n_at_dose(x, dose = 1), 3)
  expect_true(is.integer(n_at_dose(x, dose = 1)))
  expect_equal(length(n_at_dose(x, dose = 1)), 1)

  expect_equal(n_at_dose(x, dose = 'recommended'), 3)
  expect_true(is.integer(n_at_dose(x, dose = 'recommended')))
  expect_equal(length(n_at_dose(x, dose = 'recommended')), 1)

  expect_equal(n_at_recommended_dose(x), 3)
  expect_true(is.integer(n_at_recommended_dose(x)))
  expect_equal(length(n_at_recommended_dose(x)), 1)

  expect_equal(is_randomising(x), FALSE)
  expect_true(is.logical(is_randomising(x)))
  expect_equal(length(is_randomising(x)), 1)

  expect_equal(unname(prob_administer(x)), c(0.5,0.5,0,0,0))
  expect_true(is.numeric(prob_administer(x)))
  expect_equal(length(prob_administer(x)), num_doses(x))

  expect_equal(tox_at_dose(x), c(0,2,0,0,0))
  expect_true(is.integer(tox_at_dose(x)))
  expect_equal(length(tox_at_dose(x)), num_doses(x))

  expect_true(is.numeric(empiric_tox_rate(x)))
  expect_equal(length(empiric_tox_rate(x)), num_doses(x))

  expect_true(is.numeric(mean_prob_tox(x)))
  expect_equal(length(mean_prob_tox(x)), num_doses(x))

  expect_true(is.numeric(median_prob_tox(x)))
  expect_equal(length(median_prob_tox(x)), num_doses(x))

  expect_true(is.logical(dose_admissible(x)))
  expect_equal(length(dose_admissible(x)), num_doses(x))

  expect_true(is.numeric(prob_tox_quantile(x, p = 0.9)))
  expect_equal(length(prob_tox_quantile(x, p = 0.9)), num_doses(x))

  expect_true(is.numeric(prob_tox_exceeds(x, 0.5)))
  expect_equal(length(prob_tox_exceeds(x, 0.5)), num_doses(x))

  expect_true(is.logical(supports_sampling(x)))

  expect_error(prob_tox_samples(x))
  expect_error(prob_tox_samples(x, tall = TRUE))

  # Expect summary to not error. This is how that is tested, apparently:
  expect_error(summary(x), NA)
  expect_output(print(x))
  expect_true(tibble::is_tibble(as_tibble(x)))
  expect_true(nrow(as_tibble(x)) >= num_doses(x))

})

test_that('select_boin_mtd(when=finally) with stopper supports correct interface.', {

  num_doses <- 5
  target <- 0.3

  model_fitter <- get_boin(num_doses = num_doses, target = target) %>%
    stop_at_n(n = 6) %>%
    select_boin_mtd(when = 'finally')

  # Example 1, using outcome string
  x <- fit(model_fitter, '1NNN 2NTT')

  expect_equal(tox_target(x), 0.3)
  expect_true(is.numeric(tox_target(x)))

  expect_equal(num_patients(x), 6)
  expect_true(is.integer(num_patients(x)))

  expect_equal(cohort(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(cohort(x)))
  expect_equal(length(cohort(x)), num_patients(x))

  expect_equal(doses_given(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(doses_given(x)))
  expect_equal(length(doses_given(x)), num_patients(x))

  expect_equal(tox(x), c(0,0,0, 0,1,1))
  expect_true(is.integer(tox(x)))
  expect_equal(length(tox(x)), num_patients(x))

  expect_true(all((model_frame(x) - data.frame(patient = c(1,2,3,4,5,6),
                                               cohort = c(1,1,1,2,2,2),
                                               dose = c(1,1,1,2,2,2),
                                               tox = c(0,0,0,0,1,1))) == 0))
  expect_equal(nrow(model_frame(x)), num_patients(x))

  expect_equal(num_doses(x), 5)
  expect_true(is.integer(num_doses(x)))

  expect_equal(dose_indices(x), 1:5)
  expect_true(is.integer(dose_indices(x)))
  expect_equal(length(dose_indices(x)), num_doses(x))

  expect_equal(recommended_dose(x), 1)
  expect_true(is.integer(recommended_dose(x)))
  expect_equal(length(recommended_dose(x)), 1)

  expect_equal(continue(x), FALSE)
  expect_true(is.logical(continue(x)))

  expect_equal(n_at_dose(x), c(3,3,0,0,0))
  expect_true(is.integer(n_at_dose(x)))
  expect_equal(length(n_at_dose(x)), num_doses(x))

  expect_equal(n_at_dose(x, dose = 0), 0)
  expect_true(is.integer(n_at_dose(x, dose = 0)))
  expect_equal(length(n_at_dose(x, dose = 0)), 1)

  expect_equal(n_at_dose(x, dose = 1), 3)
  expect_true(is.integer(n_at_dose(x, dose = 1)))
  expect_equal(length(n_at_dose(x, dose = 1)), 1)

  expect_equal(n_at_dose(x, dose = 'recommended'), 3)
  expect_true(is.integer(n_at_dose(x, dose = 'recommended')))
  expect_equal(length(n_at_dose(x, dose = 'recommended')), 1)

  expect_equal(n_at_recommended_dose(x), 3)
  expect_true(is.integer(n_at_recommended_dose(x)))
  expect_equal(length(n_at_recommended_dose(x)), 1)

  expect_equal(is_randomising(x), FALSE)
  expect_true(is.logical(is_randomising(x)))
  expect_equal(length(is_randomising(x)), 1)

  expect_equal(unname(prob_administer(x)), c(0.5,0.5,0,0,0))
  expect_true(is.numeric(prob_administer(x)))
  expect_equal(length(prob_administer(x)), num_doses(x))

  expect_equal(tox_at_dose(x), c(0,2,0,0,0))
  expect_true(is.integer(tox_at_dose(x)))
  expect_equal(length(tox_at_dose(x)), num_doses(x))

  expect_true(is.numeric(empiric_tox_rate(x)))
  expect_equal(length(empiric_tox_rate(x)), num_doses(x))

  expect_true(is.numeric(mean_prob_tox(x)))
  expect_equal(length(mean_prob_tox(x)), num_doses(x))

  expect_true(is.numeric(median_prob_tox(x)))
  expect_equal(length(median_prob_tox(x)), num_doses(x))

  expect_true(is.logical(dose_admissible(x)))
  expect_equal(length(dose_admissible(x)), num_doses(x))

  expect_true(is.numeric(prob_tox_quantile(x, p = 0.9)))
  expect_equal(length(prob_tox_quantile(x, p = 0.9)), num_doses(x))

  expect_true(is.numeric(prob_tox_exceeds(x, 0.5)))
  expect_equal(length(prob_tox_exceeds(x, 0.5)), num_doses(x))

  expect_true(is.logical(supports_sampling(x)))

  expect_error(prob_tox_samples(x))
  expect_error(prob_tox_samples(x, tall = TRUE))

  # Expect summary to not error. This is how that is tested, apparently:
  expect_error(summary(x), NA)
  expect_output(print(x))
  expect_true(tibble::is_tibble(as_tibble(x)))
  expect_true(nrow(as_tibble(x)) >= num_doses(x))


  # Example 2, using trivial outcome string
  x <- fit(model_fitter, '')

  expect_equal(tox_target(x), 0.3)
  expect_true(is.numeric(tox_target(x)))

  expect_equal(num_patients(x), 0)
  expect_true(is.integer(num_patients(x)))

  expect_equal(cohort(x), integer(0))
  expect_true(is.integer(cohort(x)))
  expect_equal(length(cohort(x)), num_patients(x))

  expect_equal(doses_given(x), integer(0))
  expect_true(is.integer(doses_given(x)))
  expect_equal(length(doses_given(x)), num_patients(x))

  expect_equal(tox(x), integer(0))
  expect_true(is.integer(tox(x)))
  expect_equal(length(tox(x)), num_patients(x))

  expect_equal(num_tox(x), 0)
  expect_true(is.integer(num_tox(x)))

  expect_equal(dose_indices(x), 1:5)
  expect_true(is.integer(dose_indices(x)))
  expect_equal(length(dose_indices(x)), num_doses(x))

  mf <- model_frame(x)
  expect_equal(nrow(mf), 0)
  expect_equal(ncol(mf), 4)

  expect_equal(num_doses(x), 5)
  expect_true(is.integer(num_doses(x)))

  expect_equal(recommended_dose(x), 1)
  expect_true(is.integer(recommended_dose(x)))
  expect_equal(length(recommended_dose(x)), 1)

  expect_equal(continue(x), TRUE)
  expect_true(is.logical(continue(x)))

  expect_equal(n_at_dose(x), c(0,0,0,0,0))
  expect_true(is.integer(n_at_dose(x)))
  expect_equal(length(n_at_dose(x)), num_doses(x))

  expect_equal(n_at_dose(x, dose = 0), 0)
  expect_true(is.integer(n_at_dose(x, dose = 0)))
  expect_equal(length(n_at_dose(x, dose = 0)), 1)

  expect_equal(n_at_dose(x, dose = 1), 0)
  expect_true(is.integer(n_at_dose(x, dose = 1)))
  expect_equal(length(n_at_dose(x, dose = 1)), 1)

  expect_equal(n_at_dose(x, dose = 'recommended'), 0)
  expect_true(is.integer(n_at_dose(x, dose = 'recommended')))
  expect_equal(length(n_at_dose(x, dose = 'recommended')), 1)

  expect_equal(n_at_recommended_dose(x), 0)
  expect_true(is.integer(n_at_recommended_dose(x)))
  expect_equal(length(n_at_recommended_dose(x)), 1)

  expect_equal(is_randomising(x), FALSE)
  expect_true(is.logical(is_randomising(x)))
  expect_equal(length(is_randomising(x)), 1)

  expect_true(is.numeric(prob_administer(x)))
  expect_equal(length(prob_administer(x)), num_doses(x))

  expect_equal(tox_at_dose(x), c(0,0,0,0,0))
  expect_true(is.integer(tox_at_dose(x)))
  expect_equal(length(tox_at_dose(x)), num_doses(x))

  expect_true(is.numeric(empiric_tox_rate(x)))
  expect_equal(length(empiric_tox_rate(x)), num_doses(x))

  expect_true(is.numeric(mean_prob_tox(x)))
  expect_equal(length(mean_prob_tox(x)), num_doses(x))

  expect_true(is.numeric(median_prob_tox(x)))
  expect_equal(length(median_prob_tox(x)), num_doses(x))

  expect_true(is.logical(dose_admissible(x)))
  expect_equal(length(dose_admissible(x)), num_doses(x))

  expect_true(is.numeric(prob_tox_quantile(x, p = 0.9)))
  expect_equal(length(prob_tox_quantile(x, p = 0.9)), num_doses(x))

  expect_true(is.numeric(prob_tox_exceeds(x, 0.5)))
  expect_equal(length(prob_tox_exceeds(x, 0.5)), num_doses(x))

  expect_true(is.logical(supports_sampling(x)))

  expect_error(prob_tox_samples(x))
  expect_error(prob_tox_samples(x, tall = TRUE))

  # Expect summary to not error. This is how that is tested, apparently:
  expect_error(summary(x), NA)
  expect_output(print(x))
  expect_true(tibble::is_tibble(as_tibble(x)))
  expect_true(nrow(as_tibble(x)) >= num_doses(x))


  # Example 3, using tibble
  outcomes <- tibble(
    cohort = c(1,1,1, 2,2,2),
    dose = c(1,1,1, 2,2,2),
    tox = c(0,0, 0,0, 1,1)
  )
  x <- fit(model_fitter, outcomes)

  expect_equal(tox_target(x), 0.3)
  expect_true(is.numeric(tox_target(x)))

  expect_equal(num_patients(x), 6)
  expect_true(is.integer(num_patients(x)))

  expect_equal(cohort(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(cohort(x)))
  expect_equal(length(cohort(x)), num_patients(x))

  expect_equal(doses_given(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(doses_given(x)))
  expect_equal(length(doses_given(x)), num_patients(x))

  expect_equal(tox(x), c(0,0,0, 0,1,1))
  expect_true(is.integer(tox(x)))
  expect_equal(length(tox(x)), num_patients(x))

  expect_true(all((model_frame(x) - data.frame(patient = c(1,2,3,4,5,6),
                                               cohort = c(1,1,1,2,2,2),
                                               dose = c(1,1,1,2,2,2),
                                               tox = c(0,0,0,0,1,1))) == 0))
  expect_equal(nrow(model_frame(x)), num_patients(x))

  expect_equal(num_doses(x), 5)
  expect_true(is.integer(num_doses(x)))

  expect_equal(dose_indices(x), 1:5)
  expect_true(is.integer(dose_indices(x)))
  expect_equal(length(dose_indices(x)), num_doses(x))

  expect_equal(recommended_dose(x), 1)
  expect_true(is.integer(recommended_dose(x)))
  expect_equal(length(recommended_dose(x)), 1)

  expect_equal(continue(x), FALSE)
  expect_true(is.logical(continue(x)))

  expect_equal(n_at_dose(x), c(3,3,0,0,0))
  expect_true(is.integer(n_at_dose(x)))
  expect_equal(length(n_at_dose(x)), num_doses(x))

  expect_equal(n_at_dose(x, dose = 0), 0)
  expect_true(is.integer(n_at_dose(x, dose = 0)))
  expect_equal(length(n_at_dose(x, dose = 0)), 1)

  expect_equal(n_at_dose(x, dose = 1), 3)
  expect_true(is.integer(n_at_dose(x, dose = 1)))
  expect_equal(length(n_at_dose(x, dose = 1)), 1)

  expect_equal(n_at_dose(x, dose = 'recommended'), 3)
  expect_true(is.integer(n_at_dose(x, dose = 'recommended')))
  expect_equal(length(n_at_dose(x, dose = 'recommended')), 1)

  expect_equal(n_at_recommended_dose(x), 3)
  expect_true(is.integer(n_at_recommended_dose(x)))
  expect_equal(length(n_at_recommended_dose(x)), 1)

  expect_equal(is_randomising(x), FALSE)
  expect_true(is.logical(is_randomising(x)))
  expect_equal(length(is_randomising(x)), 1)

  expect_equal(unname(prob_administer(x)), c(0.5,0.5,0,0,0))
  expect_true(is.numeric(prob_administer(x)))
  expect_equal(length(prob_administer(x)), num_doses(x))

  expect_equal(tox_at_dose(x), c(0,2,0,0,0))
  expect_true(is.integer(tox_at_dose(x)))
  expect_equal(length(tox_at_dose(x)), num_doses(x))

  expect_true(is.numeric(empiric_tox_rate(x)))
  expect_equal(length(empiric_tox_rate(x)), num_doses(x))

  expect_true(is.numeric(mean_prob_tox(x)))
  expect_equal(length(mean_prob_tox(x)), num_doses(x))

  expect_true(is.numeric(median_prob_tox(x)))
  expect_equal(length(median_prob_tox(x)), num_doses(x))

  expect_true(is.logical(dose_admissible(x)))
  expect_equal(length(dose_admissible(x)), num_doses(x))

  expect_true(is.numeric(prob_tox_quantile(x, p = 0.9)))
  expect_equal(length(prob_tox_quantile(x, p = 0.9)), num_doses(x))

  expect_true(is.numeric(prob_tox_exceeds(x, 0.5)))
  expect_equal(length(prob_tox_exceeds(x, 0.5)), num_doses(x))

  expect_true(is.logical(supports_sampling(x)))

  expect_error(prob_tox_samples(x))
  expect_error(prob_tox_samples(x, tall = TRUE))

  # Expect summary to not error. This is how that is tested, apparently:
  expect_error(summary(x), NA)
  expect_output(print(x))
  expect_true(tibble::is_tibble(as_tibble(x)))
  expect_true(nrow(as_tibble(x)) >= num_doses(x))

})

test_that('select_boin_mtd(when=always) supports correct interface.', {

  num_doses <- 5
  target <- 0.3

  model_fitter <- get_boin(num_doses = num_doses, target = target) %>%
    select_boin_mtd(when = 'always')

  # Example 1, using outcome string
  x <- fit(model_fitter, '1NNN 2NTT')

  expect_equal(tox_target(x), 0.3)
  expect_true(is.numeric(tox_target(x)))

  expect_equal(num_patients(x), 6)
  expect_true(is.integer(num_patients(x)))

  expect_equal(cohort(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(cohort(x)))
  expect_equal(length(cohort(x)), num_patients(x))

  expect_equal(doses_given(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(doses_given(x)))
  expect_equal(length(doses_given(x)), num_patients(x))

  expect_equal(tox(x), c(0,0,0, 0,1,1))
  expect_true(is.integer(tox(x)))
  expect_equal(length(tox(x)), num_patients(x))

  expect_true(all((model_frame(x) - data.frame(patient = c(1,2,3,4,5,6),
                                               cohort = c(1,1,1,2,2,2),
                                               dose = c(1,1,1,2,2,2),
                                               tox = c(0,0,0,0,1,1))) == 0))
  expect_equal(nrow(model_frame(x)), num_patients(x))

  expect_equal(num_doses(x), 5)
  expect_true(is.integer(num_doses(x)))

  expect_equal(dose_indices(x), 1:5)
  expect_true(is.integer(dose_indices(x)))
  expect_equal(length(dose_indices(x)), num_doses(x))

  expect_equal(recommended_dose(x), 1)
  expect_true(is.integer(recommended_dose(x)))
  expect_equal(length(recommended_dose(x)), 1)

  expect_equal(continue(x), TRUE)
  expect_true(is.logical(continue(x)))

  expect_equal(n_at_dose(x), c(3,3,0,0,0))
  expect_true(is.integer(n_at_dose(x)))
  expect_equal(length(n_at_dose(x)), num_doses(x))

  expect_equal(n_at_dose(x, dose = 0), 0)
  expect_true(is.integer(n_at_dose(x, dose = 0)))
  expect_equal(length(n_at_dose(x, dose = 0)), 1)

  expect_equal(n_at_dose(x, dose = 1), 3)
  expect_true(is.integer(n_at_dose(x, dose = 1)))
  expect_equal(length(n_at_dose(x, dose = 1)), 1)

  expect_equal(n_at_dose(x, dose = 'recommended'), 3)
  expect_true(is.integer(n_at_dose(x, dose = 'recommended')))
  expect_equal(length(n_at_dose(x, dose = 'recommended')), 1)

  expect_equal(n_at_recommended_dose(x), 3)
  expect_true(is.integer(n_at_recommended_dose(x)))
  expect_equal(length(n_at_recommended_dose(x)), 1)

  expect_equal(is_randomising(x), FALSE)
  expect_true(is.logical(is_randomising(x)))
  expect_equal(length(is_randomising(x)), 1)

  expect_equal(unname(prob_administer(x)), c(0.5,0.5,0,0,0))
  expect_true(is.numeric(prob_administer(x)))
  expect_equal(length(prob_administer(x)), num_doses(x))

  expect_equal(tox_at_dose(x), c(0,2,0,0,0))
  expect_true(is.integer(tox_at_dose(x)))
  expect_equal(length(tox_at_dose(x)), num_doses(x))

  expect_true(is.numeric(empiric_tox_rate(x)))
  expect_equal(length(empiric_tox_rate(x)), num_doses(x))

  expect_true(is.numeric(mean_prob_tox(x)))
  expect_equal(length(mean_prob_tox(x)), num_doses(x))

  expect_true(is.numeric(median_prob_tox(x)))
  expect_equal(length(median_prob_tox(x)), num_doses(x))

  expect_true(is.logical(dose_admissible(x)))
  expect_equal(length(dose_admissible(x)), num_doses(x))

  expect_true(is.numeric(prob_tox_quantile(x, p = 0.9)))
  expect_equal(length(prob_tox_quantile(x, p = 0.9)), num_doses(x))

  expect_true(is.numeric(prob_tox_exceeds(x, 0.5)))
  expect_equal(length(prob_tox_exceeds(x, 0.5)), num_doses(x))

  expect_true(is.logical(supports_sampling(x)))

  expect_error(prob_tox_samples(x))
  expect_error(prob_tox_samples(x, tall = TRUE))

  # Expect summary to not error. This is how that is tested, apparently:
  expect_error(summary(x), NA)
  expect_output(print(x))
  expect_true(tibble::is_tibble(as_tibble(x)))
  expect_true(nrow(as_tibble(x)) >= num_doses(x))


  # Example 2, using trivial outcome string
  x <- fit(model_fitter, '')

  expect_equal(tox_target(x), 0.3)
  expect_true(is.numeric(tox_target(x)))

  expect_equal(num_patients(x), 0)
  expect_true(is.integer(num_patients(x)))

  expect_equal(cohort(x), integer(0))
  expect_true(is.integer(cohort(x)))
  expect_equal(length(cohort(x)), num_patients(x))

  expect_equal(doses_given(x), integer(0))
  expect_true(is.integer(doses_given(x)))
  expect_equal(length(doses_given(x)), num_patients(x))

  expect_equal(tox(x), integer(0))
  expect_true(is.integer(tox(x)))
  expect_equal(length(tox(x)), num_patients(x))

  expect_equal(num_tox(x), 0)
  expect_true(is.integer(num_tox(x)))

  expect_equal(dose_indices(x), 1:5)
  expect_true(is.integer(dose_indices(x)))
  expect_equal(length(dose_indices(x)), num_doses(x))

  mf <- model_frame(x)
  expect_equal(nrow(mf), 0)
  expect_equal(ncol(mf), 4)

  expect_equal(num_doses(x), 5)
  expect_true(is.integer(num_doses(x)))

  expect_equal(recommended_dose(x), 1)
  expect_true(is.integer(recommended_dose(x)))
  expect_equal(length(recommended_dose(x)), 1)

  expect_equal(continue(x), TRUE)
  expect_true(is.logical(continue(x)))

  expect_equal(n_at_dose(x), c(0,0,0,0,0))
  expect_true(is.integer(n_at_dose(x)))
  expect_equal(length(n_at_dose(x)), num_doses(x))

  expect_equal(n_at_dose(x, dose = 0), 0)
  expect_true(is.integer(n_at_dose(x, dose = 0)))
  expect_equal(length(n_at_dose(x, dose = 0)), 1)

  expect_equal(n_at_dose(x, dose = 1), 0)
  expect_true(is.integer(n_at_dose(x, dose = 1)))
  expect_equal(length(n_at_dose(x, dose = 1)), 1)

  expect_equal(n_at_dose(x, dose = 'recommended'), 0)
  expect_true(is.integer(n_at_dose(x, dose = 'recommended')))
  expect_equal(length(n_at_dose(x, dose = 'recommended')), 1)

  expect_equal(n_at_recommended_dose(x), 0)
  expect_true(is.integer(n_at_recommended_dose(x)))
  expect_equal(length(n_at_recommended_dose(x)), 1)

  expect_equal(is_randomising(x), FALSE)
  expect_true(is.logical(is_randomising(x)))
  expect_equal(length(is_randomising(x)), 1)

  expect_true(is.numeric(prob_administer(x)))
  expect_equal(length(prob_administer(x)), num_doses(x))

  expect_equal(tox_at_dose(x), c(0,0,0,0,0))
  expect_true(is.integer(tox_at_dose(x)))
  expect_equal(length(tox_at_dose(x)), num_doses(x))

  expect_true(is.numeric(empiric_tox_rate(x)))
  expect_equal(length(empiric_tox_rate(x)), num_doses(x))

  expect_true(is.numeric(mean_prob_tox(x)))
  expect_equal(length(mean_prob_tox(x)), num_doses(x))

  expect_true(is.numeric(median_prob_tox(x)))
  expect_equal(length(median_prob_tox(x)), num_doses(x))

  expect_true(is.logical(dose_admissible(x)))
  expect_equal(length(dose_admissible(x)), num_doses(x))

  expect_true(is.numeric(prob_tox_quantile(x, p = 0.9)))
  expect_equal(length(prob_tox_quantile(x, p = 0.9)), num_doses(x))

  expect_true(is.numeric(prob_tox_exceeds(x, 0.5)))
  expect_equal(length(prob_tox_exceeds(x, 0.5)), num_doses(x))

  expect_true(is.logical(supports_sampling(x)))

  expect_error(prob_tox_samples(x))
  expect_error(prob_tox_samples(x, tall = TRUE))

  # Expect summary to not error. This is how that is tested, apparently:
  expect_error(summary(x), NA)
  expect_output(print(x))
  expect_true(tibble::is_tibble(as_tibble(x)))
  expect_true(nrow(as_tibble(x)) >= num_doses(x))


  # Example 3, using tibble
  outcomes <- tibble(
    cohort = c(1,1,1, 2,2,2),
    dose = c(1,1,1, 2,2,2),
    tox = c(0,0, 0,0, 1,1)
  )
  x <- fit(model_fitter, outcomes)

  expect_equal(tox_target(x), 0.3)
  expect_true(is.numeric(tox_target(x)))

  expect_equal(num_patients(x), 6)
  expect_true(is.integer(num_patients(x)))

  expect_equal(cohort(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(cohort(x)))
  expect_equal(length(cohort(x)), num_patients(x))

  expect_equal(doses_given(x), c(1,1,1, 2,2,2))
  expect_true(is.integer(doses_given(x)))
  expect_equal(length(doses_given(x)), num_patients(x))

  expect_equal(tox(x), c(0,0,0, 0,1,1))
  expect_true(is.integer(tox(x)))
  expect_equal(length(tox(x)), num_patients(x))

  expect_true(all((model_frame(x) - data.frame(patient = c(1,2,3,4,5,6),
                                               cohort = c(1,1,1,2,2,2),
                                               dose = c(1,1,1,2,2,2),
                                               tox = c(0,0,0,0,1,1))) == 0))
  expect_equal(nrow(model_frame(x)), num_patients(x))

  expect_equal(num_doses(x), 5)
  expect_true(is.integer(num_doses(x)))

  expect_equal(dose_indices(x), 1:5)
  expect_true(is.integer(dose_indices(x)))
  expect_equal(length(dose_indices(x)), num_doses(x))

  expect_equal(recommended_dose(x), 1)
  expect_true(is.integer(recommended_dose(x)))
  expect_equal(length(recommended_dose(x)), 1)

  expect_equal(continue(x), TRUE)
  expect_true(is.logical(continue(x)))

  expect_equal(n_at_dose(x), c(3,3,0,0,0))
  expect_true(is.integer(n_at_dose(x)))
  expect_equal(length(n_at_dose(x)), num_doses(x))

  expect_equal(n_at_dose(x, dose = 0), 0)
  expect_true(is.integer(n_at_dose(x, dose = 0)))
  expect_equal(length(n_at_dose(x, dose = 0)), 1)

  expect_equal(n_at_dose(x, dose = 1), 3)
  expect_true(is.integer(n_at_dose(x, dose = 1)))
  expect_equal(length(n_at_dose(x, dose = 1)), 1)

  expect_equal(n_at_dose(x, dose = 'recommended'), 3)
  expect_true(is.integer(n_at_dose(x, dose = 'recommended')))
  expect_equal(length(n_at_dose(x, dose = 'recommended')), 1)

  expect_equal(n_at_recommended_dose(x), 3)
  expect_true(is.integer(n_at_recommended_dose(x)))
  expect_equal(length(n_at_recommended_dose(x)), 1)

  expect_equal(is_randomising(x), FALSE)
  expect_true(is.logical(is_randomising(x)))
  expect_equal(length(is_randomising(x)), 1)

  expect_equal(unname(prob_administer(x)), c(0.5,0.5,0,0,0))
  expect_true(is.numeric(prob_administer(x)))
  expect_equal(length(prob_administer(x)), num_doses(x))

  expect_equal(tox_at_dose(x), c(0,2,0,0,0))
  expect_true(is.integer(tox_at_dose(x)))
  expect_equal(length(tox_at_dose(x)), num_doses(x))

  expect_true(is.numeric(empiric_tox_rate(x)))
  expect_equal(length(empiric_tox_rate(x)), num_doses(x))

  expect_true(is.numeric(mean_prob_tox(x)))
  expect_equal(length(mean_prob_tox(x)), num_doses(x))

  expect_true(is.numeric(median_prob_tox(x)))
  expect_equal(length(median_prob_tox(x)), num_doses(x))

  expect_true(is.logical(dose_admissible(x)))
  expect_equal(length(dose_admissible(x)), num_doses(x))

  expect_true(is.numeric(prob_tox_quantile(x, p = 0.9)))
  expect_equal(length(prob_tox_quantile(x, p = 0.9)), num_doses(x))

  expect_true(is.numeric(prob_tox_exceeds(x, 0.5)))
  expect_equal(length(prob_tox_exceeds(x, 0.5)), num_doses(x))

  expect_true(is.logical(supports_sampling(x)))

  expect_error(prob_tox_samples(x))
  expect_error(prob_tox_samples(x, tall = TRUE))

  # Expect summary to not error. This is how that is tested, apparently:
  expect_error(summary(x), NA)
  expect_output(print(x))
  expect_true(tibble::is_tibble(as_tibble(x)))
  expect_true(nrow(as_tibble(x)) >= num_doses(x))

})