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Summarise calibration output over a grid of PP futility thresholds

summarize_grid_by_kappa.Rd

Applies each candidate PP futility threshold \(\kappa\) to raw replicate output (from run_paired_scenario or run_calibration_grid): a trial stops for futility if its interim PP is below \(\kappa\), otherwise it takes its continuation (D2) outcome. At kappa = 0 no trial stops, so the result is the D2 operating characteristics.

Usage

summarize_grid_by_kappa(
  raw,
  kappa_grid,
  lcb_level = 0.95,
  exclude_nonconverged = FALSE
)

Arguments

raw

A data frame with columns PP_val, continuation_success, continuation_sample_size, continuation_stop_time, sample_size_interim, t_interim and (if exclude_nonconverged = TRUE) converged.

kappa_grid

Numeric vector of candidate PP thresholds.

lcb_level

Confidence level of the one-sided exact (Clopper-Pearson) lower bound on power (default 0.95).

exclude_nonconverged

If TRUE, drop replicates whose interim MCMC did not converge (converged FALSE or NA). Default FALSE.

Value

A data frame with one row per \(\kappa\) and columns kappa, n (replicates used), n_NA_dropped (replicates dropped because PP_val was NA, with a warning), P_early_fut, power_or_typeI, power_SE, power_LCB (one-sided exact lower bound at level lcb_level, 95\ size), ESS_SE and duration (expected trial duration).

See also

select_kappa_star, compute_relative_floors