Package index • forestsearch

Core Algorithm

Main forestsearch function, subgroup selection, and consistency evaluation.

forestsearch(): ForestSearch: Exploratory Subgroup Identification
print(<forestsearch>): Print Method for forestsearch Objects
summary(<forestsearch>): Summary Method for forestsearch Objects
plot(<forestsearch>): Plot ForestSearch Results
select_best_subgroup(): Select best subgroup based on criterion
subgroup.consistency(): Evaluate Subgroup Consistency

Bootstrap Bias Correction

Bootstrap methods for bias-corrected hazard ratio estimation using infinitesimal jackknife variance estimation (Leon et al., 2024).

forestsearch_bootstrap_dofuture(): ForestSearch Bootstrap with doFuture Parallelization
summarize_bootstrap_results(): Enhanced Bootstrap Results Summary
summarize_bootstrap_events(): Summarize Bootstrap Event Counts

Cross-Validation

K-fold and repeated cross-validation for assessing subgroup identification stability and agreement metrics.

forestsearch_Kfold(): ForestSearch K-Fold Cross-Validation
forestsearch_tenfold(): ForestSearch Repeated K-Fold Cross-Validation
forestsearch_KfoldOut(): ForestSearch K-Fold Cross-Validation Output Summary
cv_summary_tables(): Create Summary Tables from forestsearch_KfoldOut Results
cv_metrics_tables(): Create Metrics Tables for Cross-Validation Results
print(<fs_kfold>): Print Method for K-Fold CV Results
print(<fs_tenfold>): Print Method for Repeated K-Fold CV Results

GRF Integration

Generalized Random Forest methods for heterogeneous treatment effect estimation and variable importance screening.

grf.subg.harm.survival(): GRF Subgroup Identification for Survival Data

Cox Model Utilities

Cox proportional hazards model wrappers with robust standard errors, spline fitting, and average hazard ratio calculations.

cox_summary(): Cox model summary for subgroup (OPTIMIZED)
cox_ahr_cde_analysis(): Comprehensive Wrapper for Cox Spline Analysis with AHR and CDE Plotting
print(<cox_ahr_cde>): Print method for cox_ahr_cde objects
summary(<cox_ahr_cde>): Summary method for cox_ahr_cde objects
cox_cs_fit(): Fit Cox Model with Cubic Spline for Treatment Effect Heterogeneity

Subgroup Tables & Estimates

Formatted tables of subgroup estimates.

sg_tables(): Enhanced Subgroup Summary Tables (gt output)
create_summary_table(): Create Enhanced Summary Table for Baseline Characteristics

Visualization

Publication-ready plotting functions for forest plots, survival curves, subgroup characteristics, and detection probability curves.

gg_forest(): ggplot2 / patchwork forest plot
plot_subgroup_results_forestplot(): Plot Subgroup Results Forest Plot
render_forestplot(): Render ForestSearch Forest Plot
create_forest_theme(): Create Forest Plot Theme with Size Controls
plot_km_band_forestsearch(): Plot Kaplan-Meier Survival Difference Bands for ForestSearch Subgroups
plot_sg_weighted_km(): Plot Weighted Kaplan-Meier Curves for ForestSearch Subgroups
figure_note(): Generate Figure Note for Quarto/RMarkdown
plot_spline_treatment_effect(): Plot Spline Treatment Effect Function
plot_detection_curve(): Plot Detection Probability Curve

Data Generating Mechanisms

Functions for creating data generating mechanisms (DGMs) for simulation studies with configurable treatment effect heterogeneity.

generate_aft_dgm_flex(): Generate Synthetic Survival Data using AFT Model with Flexible Subgroups
setup_gbsg_dgm(): Set Up a GBSG-Based AFT Data Generating Mechanism
print(<gbsg_dgm>): Print Method for gbsg_dgm Objects
compute_dgm_cde(): Compute and Attach CDE Values to a DGM Object
simulate_from_dgm(): Simulate Survival Data from AFT Data Generating Mechanism
calibrate_cens_adjust(): Calibrate Censoring Adjustment to Match DGM Reference Distribution
check_censoring_dgm(): Diagnose Censoring Consistency Between DGM Source Data and Simulated Data
calibrate_k_inter(): Calibrate k_inter for Target Subgroup Hazard Ratio
validate_k_inter_effect(): Validate k_inter Effect on HR Heterogeneity

Simulation Studies

Running and summarizing simulation studies for operating characteristics.

run_simulation_analysis(): Run One Simulation Replicate
summarize_simulation_results(): Summarize Simulation Results
format_oc_results(): Format Operating Characteristics Results as GT Table
build_classification_table(): Build Classification Rate Table from Simulation Results
build_estimation_table(): Build Estimation Properties Table from Simulation Results
interpret_estimation_table(): Generate Narrative Interpretation of Estimation Properties
render_reference_table(): Render Reference Simulation Table as gt
compute_detection_probability(): Compute Probability of Detecting True Subgroup
generate_detection_curve(): Generate Detection Probability Curve

Multi-Regional Clinical Trials

Specialized functions for multi-regional clinical trial (MRCT) subgroup analysis with regional consistency evaluation.

mrct_region_sims(): MRCT Regional Subgroup Simulation
create_dgm_for_mrct(): Create Data Generating Mechanism for MRCT Simulations

Internal

Internal implementation details. These functions are not intended to be called directly by users.

CV_sgs(): Cross-Validation Subgroup Match Summary
FS_labels(): Convert Factor Code to Label
SG_tab_estimates(): Subgroup summary table estimates
SGplot_estimates(): Violin/Boxplot Visualization of HR Estimates
acm.disjctif(): Disjunctive (dummy) coding for factor columns
add_id_column(): Add ID Column to Data Frame
add_unprocessed_vars(): Add Unprocessed Variables from Original Data
analyze_subgroup(): Analyze subgroup for summary table (OPTIMIZED)
apply_spline_constraint(): Apply Spline Constraint to Treatment Effect Coefficients
assemble_results(): Assemble Final Results Object
assign_subgroup_membership(): Assign data to subgroups based on selected node
bootstrap_results(): Bootstrap Results for ForestSearch with Bias Correction
bootstrap_ystar(): Bootstrap Ystar Matrix
build_cox_formula(): Build Cox Model Formula
calc_cov(): Calculate Covariance for Bootstrap Estimates
calculate_counts(): Calculate counts for subgroup summary
calculate_event_counts(): Calculate Event Counts by Treatment Arm
calculate_hazard_ratios(): Calculate Hazard Ratios from Potential Outcomes
calculate_linear_predictors(): Calculate Linear Predictors for Potential Outcomes
calculate_max_combinations(): Calculate Maximum Combinations
calculate_potential_hr(): Calculate potential outcome hazard ratio
calculate_skewness(): Calculate Skewness
ci_est(): Confidence Interval for Estimate
compare_detection_curves(): Compare Detection Curves Across Sample Sizes
compare_multiple_survreg(): Compare Multiple Survival Regression Models
compute_ahr(): Compute AHR from loghr_po
compute_cde(): Compute CDE from theta_0 and theta_1
compute_detection_probability_single(): Compute Detection Probability for Single Theta (Internal)
compute_node_metrics(): Compute node metrics for a policy tree
compute_sg_hr(): Compute Hazard Ratio for a Single Subgroup
compute_sg_hr_estimates(): Compute Hazard Ratio Estimates for Subgroups
compute_sg_summary(): Compute Summary Statistics for Subgroups
count_boot_id(): Count ID Occurrences in Bootstrap Sample
cox_summary_batch(): Batch Cox summaries with caching
cox_summary_vectorized(): Cox model summary for subgroup - vectorized version
create_bootstrap_caption(): Calculate Bootstrap Table Caption
create_bootstrap_diagnostic_plots(): Create Bootstrap Diagnostic Plots
create_factor_summary_tables(): Create Factor Summary Tables from Bootstrap Results
create_fs_subgroup_indicators(): Create Subgroup Indicator Columns from ForestSearch
create_gbsg_dgm(): Create GBSG-Based AFT Data Generating Mechanism
create_grf_config(): Helper Functions for GRF Subgroup Analysis
create_null_result(): Create result object when no subgroup is found
create_reference_subgroup_columns(): Create Reference Subgroup Indicator Columns
create_result_row(): Create Result Row
create_sample_size_table(): Create Sample Size Table for Multiple Scenarios
create_spline_variables(): Create Spline Variables
create_subgroup_indicator(): Create Subgroup Indicator from Factor Definitions
create_subgroup_summary_df(): Create Subgroup Summary Data Frame for Forest Plot
create_success_result(): Create result object for successful subgroup identification
create_summary_table_compact(): Preset: Compact Table
create_summary_table_minimal(): Preset: Minimal Table (No Highlighting, No Alternating)
create_summary_table_presentation(): Preset: Presentation Table (Large Fonts)
create_summary_table_publication(): Preset: Publication-Ready Table
create_timing_summary_table(): Create Timing Summary Table
cut_numeric(): Discretize Continuous Variable into Quantile-Based Categories
cut_size(): Discretize Continuous Variable by Size Categories
cut_var(): Generate cut expressions for a variable
cv_compare_results(): Compare Multiple CV Results
cv_summary_text(): Create Compact CV Summary Text
default_fs_params(): Default ForestSearch Parameters for GBSG Simulations
default_grf_params(): Default GRF Parameters for GBSG Simulations
default_grf_params_gen(): Default GRF parameters (general)
default_sim_params(): Default ForestSearch parameters (general)
define_subgroups(): Define Subgroups with Flexible Cutpoints
density_threshold_both(): Bivariate Density for Split-Sample HR Threshold Detection
density_threshold_integrand(): Vectorized Density for Integration
detect_variable_types(): Automatically Detect Variable Types in a Dataset
dummy_encode(): Dummy-code a data frame (numeric pass-through, factors expanded)
early_stop_decision(): Early Stopping Decision
evaluate_combination_with_status(): Evaluate a Single Factor Combination with Status Tracking
evaluate_comparison(): Evaluate a Comparison Expression Without eval(parse())
evaluate_consistency_twostage(): Evaluate Consistency (Two-Stage Algorithm)
evaluate_cuts_once(): Cache and validate cut expressions efficiently
evaluate_subgroup_consistency(): Evaluate Single Subgroup for Consistency (Fixed-Sample)
extract_all_tree_cuts(): Extract all cuts from fitted trees
extract_fs_estimates(): Extract Estimates from ForestSearch Results
extract_fs_subgroup_definition(): Extract Subgroup Definition from ForestSearch Object
extract_grf_estimates(): Extract Estimates from GRF Results
extract_idx_flagredundancy(): Extract redundancy flag for subgroup combinations
extract_selected_tree_cuts(): Extract cuts from selected tree only
extract_subgroup(): Extract Subgroup Information
extract_tree_cuts(): Extract cut information from a policy tree
filter_by_lassokeep(): Filter a vector by LASSO-selected variables
filter_call_args(): Filter and merge arguments for function calls
find_covariate_any_match(): Find Covariate Any Match
find_k_inter_for_target_hr(): Find k_inter Value to Achieve Target Harm Subgroup Hazard Ratio
find_leaf_split(): Find the split that leads to a specific leaf node
find_quantile_for_proportion(): Find Quantile for Target Subgroup Proportion
find_required_sample_size(): Find Minimum Sample Size for Target Detection Power
fit_aft_model(): Fit AFT Model with Optional Spline Treatment Effect
fit_aft_model_spline(): Fit AFT Model with Spline Treatment Effect
fit_aft_model_standard(): Fit Standard AFT Model (Non-Spline)
fit_causal_forest(): Fit causal survival forest
fit_cox_for_subgroup(): Fit Cox Model for Subgroup
fit_cox_models(): Fit Cox Models for Subgroups
fit_policy_trees(): Fit policy trees up to specified depth
forestsearch-package forestsearch-imports: forestsearch: Exploratory Subgroup Identification in Clinical Trials with Survival Endpoints
format_CI(): Format Confidence Interval for Estimates
format_bootstrap_diagnostics_table(): Format Bootstrap Diagnostics Table with gt
format_bootstrap_table(): Format Bootstrap Results Table with gt
format_bootstrap_timing_table(): Format Bootstrap Timing Table with gt
format_continuous_definition(): Format Continuous Variable Definition for Display
format_fs_details(): Format ForestSearch Details Output for Beamer Two-Column Display
format_results(): Format results for subgroup summary
format_search_results(): Format Search Results
format_subgroup_summary_tables(): Format Subgroup Summary Tables with gt
generate_bootstrap_synthetic(): Generate Synthetic Data using Bootstrap with Perturbation
generate_bootstrap_with_noise(): Generate Bootstrap Sample with Added Noise
generate_combination_indices(): Generate Combination Indices
generate_complement_expression(): Generate Complement Expression
generate_gbsg_bootstrap_general(): Generate Synthetic GBSG Data using Generalized Bootstrap
generate_readable_sg_labels(): Generate Readable Subgroup Labels from ForestSearch Object
generate_super_population(): Generate Super Population and Calculate Linear Predictors
get_Cox_sg(): Fit Cox Model for Subgroup
get_FSdata(): ForestSearch Data Preparation and Feature Selection
get_best_survreg(): Get Best Model from Comparison
get_bootstrap_exports(): Get all exported functions from ForestSearch namespace
get_combinations_info(): Get all combinations of subgroup factors up to maxk
get_conf_force(): Get forced cut expressions for variables
get_covs_in(): Get indicator vector for selected subgroup factors
get_cut_name(): Get variable name from cut expression
get_dfRes(): Bootstrap Confidence Interval and Bias Correction Results
get_dfpred(): Generate Prediction Dataset with Subgroup Treatment Recommendation
get_dgm_hr(): Extract HR from DGM (Backward Compatible)
get_dgm_with_output(): Create DGM with Output File Path
get_param(): Get Parameter with Default Fallback
get_split_hr_fast(): Fast Cox Model HR Estimation
get_subgroup_membership(): Get subgroup membership vector
get_targetEst(): Target Estimate and Standard Error for Bootstrap
grf.subg.eval(): GRF Subgroup Evaluation and Performance Metrics
has_positive_variance(): Check if Matrix Has Positive Variance
hrCI_format(): Format Hazard Ratio and Confidence Interval
is.continuous(): Check if a variable is continuous
is_flag_continuous(): Check if cut expression is for a continuous variable (OPTIMIZED)
is_flag_drop(): Check if cut expression should be dropped
km_summary(): KM median summary for subgroup
lasso_selection(): LASSO selection for Cox model
meets_event_criteria(): Check Event Count Criteria
meets_prevalence_threshold(): Check Prevalence Threshold
n_pcnt(): Calculate n and percent
parse_sg_harm_to_expression(): Parse sg.harm Factor Names to Expression
plot(<fs_forestplot>): Plot Method for ForestSearch Forest Plot
plot(<fs_sg_plot>): Plot Method for fs_sg_plot Objects
plot_sg_distribution(): Plot Distribution of Identified Subgroups
plot_sg_forest(): Plot Forest Plot of Hazard Ratios
plot_sg_km(): Plot Kaplan-Meier Survival Curves for Subgroups
plot_sg_results(): Plot ForestSearch Subgroup Results
plot_sg_summary_panel(): Plot Summary Statistics Panel
plot_subgroup(): Plot Subgroup Survival Curves
plot_subgroup_effects(): Plot Subgroup Analysis Results
prepare_censoring_model(): Prepare Censoring Model Parameters
prepare_search_data(): Prepare Data for Subgroup Search
prepare_subgroup_data(): Prepare subgroup data for analysis
prepare_working_dataset(): Prepare Working Dataset with Processed Covariates
print(<fs_forest_theme>): Print Method for ForestSearch Forest Theme
print(<fs_forestplot>): Print Method for ForestSearch Forest Plot
print(<fs_sg_plot>): Print Method for fs_sg_plot Objects
print(<fs_weighted_km>): Print Method for fs_weighted_km Objects
print(<multi_survreg_comparison>): Print method for survreg_comparison objects
print_cv_params(): Print CV ForestSearch Parameters
print_grf_details(): Print detailed output for debugging
process_conf_force_expr(): Process forced cut expression for a variable
process_continuous_subgroup(): Process Continuous Variable for Subgroup Definition
process_continuous_vars(): Process Continuous Variables
process_cutpoint(): Process Cutpoint Specification for Subgroup Definition
process_factor_subgroup(): Process Factor Variable for Subgroup Definition
process_factor_vars(): Process Factor Variables with Largest Value as Reference
qhigh(): 75th Percentile (Quantile High)
qlow(): 25th Percentile (Quantile Low)
quick_km_band_plot(): Quick Plot KM Bands from ForestSearch
remove_near_duplicate_subgroups(): Remove Near-Duplicate Subgroups
remove_redundant_subgroups(): Remove Redundant Subgroups
resolve_bootstrap_parallel_args(): Resolve parallel processing arguments for bootstrap
resolve_cv_parallel_args(): Resolve Parallel Arguments for Cross-Validation
rmst_calculation(): RMST calculation for subgroup
run_forestsearch_analysis(): Run ForestSearch Analysis
run_grf_analysis(): Run GRF Analysis
run_single_consistency_split(): Run Single Consistency Split
safe_eval_expr(): Evaluate an expression string in a data-frame scope
safe_subset(): Subset a data frame using an expression string
save_forestplot(): Save ForestSearch Forest Plot to File
sens_text(): Generate Cross-Validation Sensitivity Text
sensitivity_analysis_k_inter(): Sensitivity Analysis of Hazard Ratios to k_inter
setup_parallel_SGcons(): Set up parallel processing for subgroup consistency
sg_consistency_out(): Output Subgroup Consistency Results
simulate_from_gbsg_dgm(): Simulate Trial Data from GBSG DGM
sort_subgroups(): Sort Subgroups by Focus
sort_subgroups_preview(): Sort Subgroups by Focus at consistency stage (consistency not available at this point)
subgroup.search(): Subgroup Search for Treatment Effect Heterogeneity (Improved, Parallelized)
summarize_bootstrap_subgroups(): Summarize Bootstrap Subgroup Analysis Results
summarize_factor_presence_robust(): Summarize Factor Presence Across Bootstrap Subgroups
summarize_single_analysis(): Summarize Single Analysis Results
summaryout_mrct(): Summary Tables for MRCT Simulation Results
validate_grf_data(): Validate input data for GRF analysis
validate_inputs(): Validate Input Parameters
validate_mrct_data(): Validate Dataset for MRCT Simulations
validate_spline_spec(): Validate Spline Specification
wilson_ci(): Wilson Score Confidence Interval