Simulated trials.
This class encapsulates that many notional or virtual trials can be simulated. Each recommends a dose (or doses), keeps track of how many patients have been treated at what doses, what toxicity outcomes have been seen, and whether a trial advocates continuing, etc. We run simulations to learn about the operating characteristics of a trial design.
Computationally, the simulations class supports much of the same
interface as selector, and a little more.
Thus, many of the same generic functions are supported - see Examples.
However, compared to selectors, the returned objects reflect
that there are many trials instead of one, e.g. num_patients(sims),
returns as an integer vector the number of patients used in the simulated
trials.
simulations(fits, true_prob_tox, true_prob_eff = NULL, ...)
fits |
Simulated model fits, arranged as list of lists. |
true_prob_tox |
vector of true toxicity probabilities |
true_prob_eff |
vector of true efficacy probabilities, optionally NULL if efficacy not analysed. |
... |
Extra args |
The simulations object implements the following functions:
list with slots: fits containing model fits;
and true_prob_tox, contianing the assumed true probability of
toxicity.
# Simulate performance of the 3+3 design: true_prob_tox <- c(0.12, 0.27, 0.44, 0.53, 0.57) sims <- get_three_plus_three(num_doses = 5) %>% simulate_trials(num_sims = 10, true_prob_tox = true_prob_tox) # The returned object has type 'simulations'. The supported interface is: sims %>% num_patients() sims %>% num_doses() sims %>% dose_indices() sims %>% n_at_dose() sims %>% tox_at_dose() sims %>% num_tox() sims %>% recommended_dose() sims %>% prob_administer() sims %>% prob_recommend() sims %>% trial_duration() # Access the list of model fits for the ith simulated trial using: i <- 1 sims$fits[[i]] # and the jth model fit for the ith simulated trial using: j <- 1 sims$fits[[i]][[j]] # and so on.
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