Building Cox Models

Functions for building penalized Cox models.

fit_lasso()

Model selection for high-dimensional Cox models with lasso penalty

fit_alasso()

Model selection for high-dimensional Cox models with adaptive lasso penalty

fit_enet()

Model selection for high-dimensional Cox models with elastic-net penalty

fit_aenet()

Model selection for high-dimensional Cox models with adaptive elastic-net penalty

fit_scad()

Model selection for high-dimensional Cox models with SCAD penalty

fit_snet()

Model selection for high-dimensional Cox models with Snet penalty

fit_mcp()

Model selection for high-dimensional Cox models with MCP penalty

fit_mnet()

Model selection for high-dimensional Cox models with Mnet penalty

fit_flasso()

Model selection for high-dimensional Cox models with fused lasso penalty

print(<hdnom.model>)

Print high-dimensional Cox model objects

predict(<hdnom.model>)

Make predictions from high-dimensional Cox models

infer_variable_type()

Extract information of selected variables from high-dimensional Cox models

Nomogram Visualization

Functions for nomogram visualization of the penalized Cox models

as_nomogram()

Construct nomogram ojects for high-dimensional Cox models

print(<hdnom.nomogram>)

Print nomograms objects

plot(<hdnom.nomogram>)

Plot nomogram objects

Model Validation

Functions for model validation using bootstrap, k-fold cross-validation, and repeated k-fold cross-validation. Model performance is assessed by time-dependent AUC (tAUC).

validate()

Validate high-dimensional Cox models with time-dependent AUC

print(<hdnom.validate>)

Print validation results

summary(<hdnom.validate>)

Summary of validation results

plot(<hdnom.validate>)

Plot optimism-corrected time-dependent discrimination curves for validation

validate_external()

Externally validate high-dimensional Cox models with time-dependent AUC

print(<hdnom.validate.external>)

Print external validation results

summary(<hdnom.validate.external>)

Summary of external validation results

plot(<hdnom.validate.external>)

Plot time-dependent discrimination curves for external validation

Model Calibration

Functions for model calibration using direct fitting, bootstrap resampling, k-fold cross-validation, and repeated cross-validation.

calibrate()

Calibrate high-dimensional Cox models

print(<hdnom.calibrate>)

Print calibration results

summary(<hdnom.calibrate>)

Summary of calibration results

plot(<hdnom.calibrate>)

Plot calibration results

calibrate_external()

Externally calibrate high-dimensional Cox models

print(<hdnom.calibrate.external>)

Print external calibration results

summary(<hdnom.calibrate.external>)

Summary of external calibration results

plot(<hdnom.calibrate.external>)

Plot external calibration results

kmplot()

Kaplan-Meier plot with number at risk table for internal calibration and external calibration results

logrank_test()

Log-rank test for internal calibration and external calibration results

Model Comparison

Functions for model comparison in terms of validation and calibration performance.

compare_by_validate()

Compare high-dimensional Cox models by model validation

print(<hdnom.compare.validate>)

Print model comparison by validation results

summary(<hdnom.compare.validate>)

Summary of model comparison by validation results

plot(<hdnom.compare.validate>)

Plot model comparison by validation results

compare_by_calibrate()

Compare high-dimensional Cox models by model calibration

print(<hdnom.compare.calibrate>)

Print model comparison by calibration results

summary(<hdnom.compare.calibrate>)

Summary of model comparison by calibration results

plot(<hdnom.compare.calibrate>)

Plot model comparison by calibration results

Miscellaneous

Miscellaneous functions for supporting survival analysis, such as baseline hazard estimation and survival curve prediction.

theme_hdnom()

Plot theme (ggplot2) for hdnom

glmnet_basesurv()

Breslow baseline hazard estimator for glmnet objects

glmnet_survcurve()

Survival curve prediction for glmnet objects

ncvreg_basesurv()

Breslow baseline hazard estimator for ncvreg objects

ncvreg_survcurve()

Survival curve prediction for ncvreg objects

penalized_basesurv()

Breslow baseline hazard estimator for penfit objects

penalized_survcurve()

Survival curve prediction for penfit objects

hdnom-package

hdnom: Benchmarking and Visualization Toolkit for Penalized Cox Models

Datasets

Example datasets

smart

Imputed SMART study data

smarto

Original SMART study data