Frequentist Dynamic Borrowing for Hybrid-Control Survival Trials

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Documentation for package ‘fdb’ version 0.2.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

fdb-package	fdb: Frequentist Dynamic Borrowing for Hybrid-Control Survival Trials
add_ess_to_simulation_result	Append ESS to a simulation summary
calibrate_all_lambdas	Calibrate lambda for all borrowing methods
calibrate_lambda_grid	Single-stage lambda calibration for one borrowing method
calibrate_lambda_grid_two_stage	Two-stage lambda calibration for one borrowing method
compute_ess_from_raw	Compute effective sample size from raw simulation output
compute_sandwich_se	Sandwich standard error for a penalized Cox borrowing estimator
drift_set	Drift set utilities
fdb	fdb: Frequentist Dynamic Borrowing for Hybrid-Control Survival Trials
fit_all_methods	Fit all borrowing methods on a single dataset
fit_internal_only	Internal-control-only Cox analysis
fit_li_adaptive_lasso	Adaptive lasso borrowing of Li et al. (2023)
fit_naive_pooled	Naive pooled Cox analysis
fit_one_penalized_method	Fit a single penalized borrowing method
fit_P1_precision_L1	Precision-weighted L1 penalty (P1)
fit_P2_gated_L1	Smoothed integrated-gate penalty (P2)
fit_P3_info_MCP	Information-adaptive minimax concave penalty (P3)
fit_P4_LRweighted_L1	Likelihood-ratio-weighted L1 penalty (P4)
lambdas_default	Default tuning parameters
make_drift_set	Drift set utilities
make_drift_set_from_values	Drift set utilities
run_drift_curve	Evaluate operating characteristics across a set of drift values
run_fdb_study	One-stop wrapper: calibrate lambda, then evaluate type I and power
run_simulation	Run a Monte Carlo simulation under a fixed scenario
scenario_S1	Example simulation scenario
simulate_hybrid_cox	Simulate a hybrid-control Cox proportional hazards dataset