benchmark_leakage_suite: Simulation benchmark matrix for leakage diagnostics

In bioLeak: Leakage-Safe Modeling and Auditing for Genomic and Clinical Data

Simulation benchmark matrix for leakage diagnostics

Description

Runs a reproducible grid of simulation scenarios across modalities, leakage mechanisms, and split modes using [simulate_leakage_suite()]. This function is designed as a benchmarking harness to quantify detection rates and performance inflation under controlled settings.

Usage

benchmark_leakage_suite(
  modalities = c("omics", "imaging_tabular", "ehr_tabular"),
  leakages = c("none", "subject_overlap", "batch_confounded", "peek_norm", "lookahead"),
  modes = c("subject_grouped", "batch_blocked", "time_series"),
  learner = c("glmnet", "ranger"),
  seeds = 1:5,
  B = 200,
  alpha = 0.05,
  parallel = FALSE
)

Arguments

modalities	Character vector selecting predefined modality profiles. Supported values: '"omics"', '"imaging_tabular"', '"ehr_tabular"'.
leakages	Character vector of leakage mechanisms passed to [simulate_leakage_suite()].
modes	Character vector of split modes passed to [simulate_leakage_suite()].
learner	Character scalar. '"glmnet"' (default) or '"ranger"'.
seeds	Integer vector of Monte Carlo seeds.
B	Integer scalar. Number of permutations per scenario.
alpha	Numeric scalar in (0, 1). Detection threshold applied to permutation p-values.
parallel	Logical scalar. If TRUE, evaluates scenarios in parallel when 'future.apply' is available.

Value

A data.frame with one row per simulation seed/scenario and columns: 'modality', 'leakage', 'mode', 'seed', observed metric, gap, p-value, and a logical 'detected' flag. A scenario-level summary is attached as 'attr(x, "summary")'.

bioLeak documentation built on March 6, 2026, 1:06 a.m.