Nothing
## -----------------------------------------------------------------------------
outcomes <- '2NN 3NN 4TT'
## -----------------------------------------------------------------------------
skeleton <- c(0.05, 0.15, 0.25, 0.4, 0.6)
target <- 0.25
## ---- message=FALSE, warning=FALSE--------------------------------------------
library(trialr)
## ---- results = "hide", warning=FALSE, message=FALSE--------------------------
fit <- stan_crm(outcomes, skeleton = skeleton, target = target,
beta_sd = sqrt(1.34), seed = 123)
fit
## ---- warning=FALSE, message=FALSE--------------------------------------------
library(dplyr)
library(tidybayes)
prob_tox_samp_tall <- fit %>%
gather_draws(prob_tox[dose]) %>%
rename(prob_dlt = .value) %>%
ungroup
## -----------------------------------------------------------------------------
prob_tox_samp_tall %>% head(10)
## ---- fig.width=7, fig.height=7-----------------------------------------------
library(ggplot2)
prob_tox_samp_tall %>%
ggplot(aes(x = dose, y = prob_dlt, group = dose)) +
geom_boxplot() +
ylim(0, 1) +
labs(title = 'Boxplot of Prob(DLT) under CRM')
## ---- fig.width=7, fig.height=7-----------------------------------------------
prob_tox_samp_tall %>%
ggplot(aes(x = dose, y = prob_dlt, group = dose)) +
geom_violin(fill = 'orange') +
ylim(0, 1) +
labs(title = 'Violin plot of Prob(DLT) under CRM')
## ---- fig.width=7, fig.height=7, message=FALSE--------------------------------
library(ggridges)
prob_tox_samp_tall %>%
mutate(dose = factor(dose)) %>%
ggplot(aes(x = prob_dlt, y = dose, fill = dose)) +
geom_density_ridges() +
theme(legend.position = 'none') +
labs(title = 'Joyplot of Prob(DLT) under CRM') +
theme(legend.position = 'bottom')
## ---- fig.width=7, fig.height=7, message=FALSE--------------------------------
prob_tox_samp_tall %>%
group_by(.draw) %>%
summarise(mtd = dose[which.min(abs(prob_dlt - target))]) %>%
mutate(mtd = factor(mtd)) -> mtd_candidates
prob_tox_samp_tall %>%
left_join(mtd_candidates, by = '.draw') %>%
filter(.draw <= 200) %>%
ggplot(aes(x = dose, y = prob_dlt, group = .draw)) +
geom_line(aes(col = mtd), alpha = 0.5) +
geom_hline(yintercept = target, col = 'red', linetype = 'dashed') +
labs(title = 'The identify of the MTD is still shrouded in mystery',
y = 'Prob(DLT)', col = 'MTD') +
theme(legend.position = 'bottom')
## ---- fig.width=7, fig.height=7, message=FALSE, warning=FALSE-----------------
mtd_candidates %>%
count(mtd) %>%
mutate(prob_mtd = n / sum(n)) %>%
ggplot(aes(x = mtd, y = prob_mtd, fill = mtd)) +
geom_col() +
labs(x = 'MTD') +
theme(legend.position = 'bottom')
## ---- fig.width=7, fig.height=7-----------------------------------------------
fit %>%
gather_draws(prob_tox[dose]) %>%
group_by(dose) %>%
summarise(prob_too_toxic = mean(.value > target)) %>%
ggplot(aes(x = dose, y = prob_too_toxic, fill = dose)) +
geom_col() +
scale_fill_gradient(low="green", high="red") +
labs(title = 'Posterior probability that each dose is too toxic',
y = 'Prob(DLT risk > target)', fill = 'Probability dose is too toxic') +
theme(legend.position = 'bottom')
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