trialr (version 0.0.7)

model_BebopInPeps2: Stan model for BEBOP implementation in PePS2 clinical trial

Description

This is the Stan implementation of the BEBOP design for the PePS2 trial, that incorporates baseline predictive information to study co-primary efficacy and toxicity outcomes.

The model is compiled when trialr is installed and is available at run-time under stanmodels$BebopInPeps2.

The design has been submitted for publication by Brock et al. in 2017.

See the BEBOP vignette for a detailed description of the probability model and a demonstration of the pertinent methods implemented in trial.

See Also

peps2_params

peps2_get_data

peps2_process

Examples

# NOT RUN {
# Get model parameters as used in the PePS2 trial.
# This call randomly samples patient outcomes so set a seed
set.seed(123)
dat <- peps2_get_data(num_patients = 60,
                     prob_eff = c(0.167, 0.192, 0.5, 0.091, 0.156, 0.439),
                     prob_tox = rep(0.1, 6),
                     eff_tox_or = rep(1, 6))
# Fit the observed data to the model using rstan
samp <- rstan::sampling(stanmodels$BebopInPeps2, data = dat)
# The fit object is quite crude. Post-process to perform useful inference:
decision <- peps2_process(dat, samp)
decision$Accept   # Accept in cohort 2, 3, 5, 6 but not 1 or 4
decision$ProbEff  # The probability of efficacy is driving that decision
# }