Run Sensitivity

Small-sample Bayesian meta-analysis can be prior-sensitive and uncertainty-sensitive. For serious reporting, sensitivity is part of the result.

Enable prior sensitivity

sensitivity:
  prior: true

When prior_specs are omitted, the package uses a scale-aware grid:

• log_relative: regularising, default, weak
• percentage_point: regularising, default, weak

Review prior_sensitivity.csv for pooled mean, probability positive, interval width, diagnostics, and deltas versus the default prior.

Enable uncertainty sensitivity

sensitivity:
  uncertainty: true

Rows with source-derived uncertainty keep that uncertainty. Rows with uncertainty_scenario use the configured low, medium, or high model-scale standard error.

Scenario assumptions live in:

uncertainty:
  scenario_standard_errors:
    log_relative:
      low: 0.03
      medium: 0.08
      high: 0.15
    percentage_point:
      low: 1.0
      medium: 3.0
      high: 5.0

Report when reasonable sensitivity settings change the substantive conclusion.