dot-compute_assurance: Compute Mean Assurance for a Given Metric (Multi-Effect...

In powerbrmsINLA: Bayesian Power Analysis Using 'brms' and 'INLA'

Compute Mean Assurance for a Given Metric (Multi-Effect Compatible) Summarises simulation results and computes proportion passing for decision rule metric.

Description

Compute Mean Assurance for a Given Metric (Multi-Effect Compatible) Summarises simulation results and computes proportion passing for decision rule metric.

Usage

.compute_assurance(
  df,
  metric,
  prob_threshold,
  rope_rule = c(">="),
  direction_p = 0.5,
  effect_cols = NULL
)

Arguments

df	Data frame containing simulation results with columns n, effect cols, ok, and metric columns.
metric	One of "direction", "threshold", "rope".
prob_threshold	Numeric, threshold for "threshold" and "rope" metrics.
rope_rule	Reserved for future use.
direction_p	Numeric cutoff for "direction" metric (default 0.5).
effect_cols	Optional character vector of effect columns to group by. If NULL, auto-detects "true_effect" or others.

Value

Tibble grouped by n and effects with assurance column.

powerbrmsINLA documentation built on July 2, 2026, 5:07 p.m.