eval_thresh: Evaluate a single dataset for a single pp_threshold and ppp_threshold combination

Description

Helper function for calibrate_thresholds() function that evaluates a single combination of a pp_threshold and a ppp_threshold for a single dataset

Usage

eval_thresh(
  data,
  pp_threshold,
  ppp_threshold,
  p0,
  N,
  direction = "greater",
  delta = NULL,
  monitoring = "futility",
  prior = c(0.5, 0.5),
  S = 5000
)

Value

Returns a tibble with the total sample size at the end of the trial, the number of responses observed at the end of the trial, the pp_threshold considered, the ppp_threshold considered, the observed predictive probability generated from calc_predictive(), and an indicator for whether the trial was positive or not at the end

Arguments

data: the name of the dataset
pp_threshold: the posterior probability threshold of interest
ppp_threshold: the posterior probability threshold of interest for futility monitoring
p0: The target value to compare to in the one-sample case. Set to NULL for the two-sample case.
N: the total planned sample size at the end of the trial, c(N0, N1) for two-sample case; integer of total planned sample size at end of trial N for one-sample case
direction: "greater" (default) if interest is in P(p1 > p0) and "less" if interest is in P(p1 < p0) for two-sample case. For one-sample case, "greater" if interest is in P(p > p0) and "less" if interest is in P(p < p0).
delta: clinically meaningful difference between groups. Typically 0 for the two-sample case. NULL for the one-sample case (default).
monitoring: the type of interim monitoring to be performed. One of "futility" or "efficacy". Default is "futility".
prior: hyperparameters of prior beta distribution. Beta(0.5, 0.5) is default
S: number of samples, default is 5000