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Draws one point per method and parameter combination, placing the operating characteristic against the type I error rate that method incurs, so that methods can be compared at the error rate they actually spend rather than at their nominal one.

Usage

operating_characteristic_vs_tie(
  results_metrics_df,
  case_study,
  target_sample_size_per_arm,
  treatment_effect,
  operating_characteristic,
  source_denominator_change_factor,
  target_to_source_std_ratio,
  show_tie_error_bars = FALSE
)

Arguments

results_metrics_df

The dataframe containing the results and metrics.

case_study

The case study name.

target_sample_size_per_arm

The target sample size per arm.

treatment_effect

The treatment effect scenario ("consistent", "no_effect" or "partially_consistent").

operating_characteristic

The metric to plot, as an entry of frequentist_metrics or inference_metrics.

source_denominator_change_factor

The source denominator change factor.

target_to_source_std_ratio

The target to source standard deviation ratio.

show_tie_error_bars

Whether to draw the Monte Carlo interval on the type I error axis.

Value

None