Bootstrap confidence intervals for GLS consensus effects — bootstrap_consensus

Uses matched subject-bootstrap layer-effect draws from `bootstrap_effect_covariance()` and the fitted covariance structure to form a bootstrap distribution of the GLS consensus effect. The hypothesis tests and analytic standard errors remain unchanged; these intervals are intended for robust uncertainty reporting and coverage validation.

Usage

bootstrap_consensus_intervals(
  effects,
  bootstrap,
  integrated = NULL,
  method = c("percentile", "basic"),
  conf_level = 0.95,
  min_boot = 100L,
  min_omics = 2L
)

Arguments

effects: Layer-specific effect table.
bootstrap: An `omics_braid_covariance` object.
integrated: Optional output of `integrate_effects()`.
method: `"percentile"` or `"basic"`.
conf_level: Confidence level.
min_boot: Minimum usable bootstrap consensus draws.
min_omics: Minimum finite omic layers required in an individual bootstrap replicate.

Value

One row per entity with bootstrap consensus interval diagnostics.