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voiage.cli.calculate_adaptive_evsi

calculate_adaptive_evsi

Section titled “calculate_adaptive_evsi”
calculate_adaptive_evsi([positional or keyword] parameter_file: Path = typer.Argument(..., exists=True, file_okay=True, dir_okay=False, readable=True, help='Path to CSV containing PSA parameters (samples x parameters)'), [positional or keyword] trial_design_file: Path = typer.Argument(..., exists=True, file_okay=True, dir_okay=False, readable=True, help='Path to JSON trial design with arm definitions'), [positional or keyword] adaptive_rules_file: Path = typer.Option(..., '--adaptive-rules', exists=True, file_okay=True, dir_okay=False, readable=True, help='Path to JSON adaptive rules specification'), [positional or keyword] simulator: str = typer.Option('bayesian', '--simulator', help='Adaptive simulator to use: bayesian or sophisticated'), [positional or keyword] population: float | None = typer.Option(None, '--population', help='Population size for population-adjusted EVSI'), [positional or keyword] discount_rate: float | None = typer.Option(None, '--discount-rate', help='Annual discount rate (e.g., 0.03)'), [positional or keyword] time_horizon: float | None = typer.Option(None, '--time-horizon', help='Time horizon in years'), [positional or keyword] n_outer_loops: int = typer.Option(10, '--n-outer-loops', help='Outer Monte Carlo loops'), [positional or keyword] n_inner_loops: int = typer.Option(50, '--n-inner-loops', help='Inner Monte Carlo loops'), [positional or keyword] output_file: Path | None = typer.Option(None, '--output', '-o', help='File to save adaptive EVSI result')) -> None

Calculate Expected Value of Sample Information for adaptive trial designs.

Examples

Section titled “Examples”

Calculate adaptive EVSI from parameters, a trial design, and rules:

.. code-block:: bash

voiage calculate-adaptive-evsi parameters.csv trial_design.json –adaptive-rules adaptive_rules.json

Parameters:

  • parameter_file Path (default: typer.Argument(..., exists=True, file_okay=True, dir_okay=False, readable=True, help='Path to CSV containing PSA parameters (samples x parameters)'))
  • trial_design_file Path (default: typer.Argument(..., exists=True, file_okay=True, dir_okay=False, readable=True, help='Path to JSON trial design with arm definitions'))
  • adaptive_rules_file Path (default: typer.Option(..., '--adaptive-rules', exists=True, file_okay=True, dir_okay=False, readable=True, help='Path to JSON adaptive rules specification'))
  • simulator str (default: typer.Option('bayesian', '--simulator', help='Adaptive simulator to use: bayesian or sophisticated'))
  • population float | None (default: typer.Option(None, '--population', help='Population size for population-adjusted EVSI'))
  • discount_rate float | None (default: typer.Option(None, '--discount-rate', help='Annual discount rate (e.g., 0.03)'))
  • time_horizon float | None (default: typer.Option(None, '--time-horizon', help='Time horizon in years'))
  • n_outer_loops int (default: typer.Option(10, '--n-outer-loops', help='Outer Monte Carlo loops'))
  • n_inner_loops int (default: typer.Option(50, '--n-inner-loops', help='Inner Monte Carlo loops'))
  • output_file Path | None (default: typer.Option(None, '--output', '-o', help='File to save adaptive EVSI result'))

Returns: None