View source: R/efftox_simulate.R
efftox_simulate | R Documentation |
Run EffTox simulations for assumed true efficacy and toxicity curves.
efftox_simulate(
dat,
num_sims,
first_dose,
true_eff,
true_tox,
cohort_sizes,
...
)
dat |
An instance of |
num_sims |
integer, number of simulated iterations |
first_dose |
integer, the dose-level to give to patient 1, e.g. 1 for the lowest dose. |
true_eff |
the true probabilities of efficacy at the doses under investigation; a vector of numbers between 0 and 1. |
true_tox |
the true probabilities of toxicity at the doses under investigation; a vector of numbers between 0 and 1. |
cohort_sizes |
a vector of integer cohort sizes. A dose decision is made
when each cohort is completed and the next cohort is treated at the
recommended dose. To conduct a trial using at most 20 patients, where dose is
re-evaluated after every second patient, use |
... |
Extra parameters provided via the ellipsis are passed to
|
A list with named elements recommended_dose
,
efficacies
, toxicities
, and doses_given
.
dat <- efftox_parameters_demo()
set.seed(123)
# Let's say we want to use only 2 chains. Extra args are passed to stan
## Not run:
sims <- efftox_simulate(dat, num_sims = 10, first_dose = 1,
true_eff = c(0.20, 0.40, 0.60, 0.80, 0.90),
true_tox = c(0.05, 0.10, 0.15, 0.20, 0.40),
cohort_sizes = rep(3, 13),
chains = 2)
table(sims$recommended_dose) / length(sims$recommended_dose)
table(unlist(sims$doses_given)) / length(unlist(sims$doses_given))
table(unlist(sims$doses_given)) / length(sims$recommended_dose)
## End(Not run)
# In real life, we would run thousands of iterations, not 10.
# This is an example.
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