Determine operating characteristics of fits from two-arm trials with an exponentially distributed time-to-event endpoint and no predictor of the intercurrent event

Usage

ocs_exp_nocovar(multiple_fits, d_params, m_params)

Arguments

multiple_fits: List of model fits from fit_mult_exp_nocovar.
d_params: List of data parameters as used in sim_dat_one_trial_exp_nocovar.
m_params: List of model parameters as used in fit_single_exp_nocovar.

Value

A list of length 3, containing objects call ocs, d_params, m_params, where ocs is a tibble containing averaged parameter estimates and operating characteristics, and d_params and m_params are the objects supplied to the function.

Details

This function is used in run_sim_exp_nocovar(), the output of the two functions is the same.

Examples

d_params_nocovar <- list(
  n = 500L,
  nt = 250L,
  prob_ice = 0.5,
  fu_max = 336L,
  prop_cens = 0.15,
  T0T_rate = 0.2,
  T0N_rate = 0.2,
  T1T_rate = 0.15,
  T1N_rate = 0.1
)
dat_mult_trials <- sim_dat_mult_trials_exp_nocovar(
  n_iter = 2,
  params = d_params_nocovar 
)
m_params_nocovar <- list(
  tg = 48L,
  prior_piT = c(0.5, 0.5),
  prior_0N = c(1.5, 5),
  prior_1N = c(1.5, 5),
  prior_0T = c(1.5, 5),
  prior_1T = c(1.5, 5),
  t_grid =  seq(7, 7 * 48, 7) / 30,
  chains = 2L,
  n_iter = 3000L,
  warmup = 1500L,
  cores = 2L,
  open_progress = FALSE,
  show_messages = TRUE  
)
# \donttest{
fit_multiple <- fit_mult_exp_nocovar(
  dat_mult_trials = dat_mult_trials,
  params = m_params_nocovar,
  seed = 12
)
list_ocs <- ocs_exp_nocovar(
  multiple_fits = fit_multiple, 
  d_params = d_params_nocovar, 
  m_params = m_params_nocovar
)
print(list_ocs)
# }