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hdnom

hdnom creates nomogram visualizations for penalized Cox regression models, with the support of reproducible survival model building, validation, calibration, and comparison for high-dimensional data.

Installation

You can install hdnom from CRAN:

install.packages("hdnom")

Or try the development version on GitHub:

remotes::install_github("nanxstats/hdnom")

Browse the vignettes to get started.

Gallery

Nomogram

Kaplan-Meier plot with number at risk table

Model validation and calibration

Model comparison by validation or calibration

Shiny app

Contribute

To contribute to this project, please take a look at the Contributing Guidelines first. Please note that the hdnom project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

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Version

Install

install.packages('hdnom')

Monthly Downloads

418

Version

6.1.0

License

GPL-3 | file LICENSE

Issues

1

Pull Requests

0

Stars

43

Forks

11

Maintainer

Nan Xiao

Last Published

June 9th, 2025

Functions in hdnom (6.1.0)

glmnet_validate_external_tauc

Compute external validation measures for glmnet objects
infer_variable_type

Extract information of selected variables from high-dimensional Cox models
plot.hdnom.compare.calibrate

Plot model comparison by calibration results
plot.hdnom.calibrate

Plot calibration results
logrank_test

Log-rank test for internal calibration and external calibration results
glmnet_validate_tauc

Compute validation measures for glmnet objects
plot.hdnom.calibrate.external

Plot external calibration results
ncvreg_survcurve

Survival curve prediction for ncvreg objects
fit_lasso

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

Color Palette for AAAS Journals
ncvreg_validate_tauc

Compute validation measures for ncvreg model objects
penalized_validate_tauc

Compute validation measures for penfit model objects
penalized_basesurv

Breslow baseline hazard estimator for penfit objects
penalized_survcurve

Survival curve prediction for penfit objects
ncvreg_calibrate_surv_prob_pred

Compute ncvreg predicted survival probabilities for calibration
ncvreg_validate_external_tauc

Compute external validation measures for ncvreg model objects
palette_lancet

Color Palette for Lancet Journals
hdnom-package

hdnom: Benchmarking and Visualization Toolkit for Penalized Cox Models
kmplot_raw

Kaplan-Meier Plot with Number at Risk Table
penalized_calibrate_surv_prob_pred

Compute penfit predicted survival probabilities for calibration
palette_npg

Color Palette for NPG Journals
fit_mnet

Model selection for high-dimensional Cox models with Mnet penalty
penalized_calibrate_external_surv_prob_pred

Compute penfit predicted survival probabilities for external calibration
palette_jco

Color Palette for Journal of Clinical Oncology (JCO)
ncvreg_basesurv

Breslow baseline hazard estimator for ncvreg objects
penalized_tune_lambda

Automatic lambda tuning function for fused lasso by k-fold cross-validation
ncvreg_calibrate_external_surv_prob_pred

Compute ncvreg predicted survival probabilities for external calibration
plot.hdnom.nomogram

Plot nomogram objects
plot.hdnom.compare.validate

Plot model comparison by validation results
print.hdnom.compare.calibrate

Print model comparison by calibration results
print.hdnom.calibrate.external

Print external calibration results
smarto

Original SMART study data
predict.hdnom.model

Make predictions from high-dimensional Cox models
penalized_validate_external_tauc

Compute external validation measures for penfit model objects
summary.hdnom.compare.validate

Summary of model comparison by validation results
summary.hdnom.calibrate

Summary of calibration results
kmplot

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

Automatic MCP/SCAD gamma tuning function by k-fold cross-validation
print.hdnom.model

Print high-dimensional Cox model objects
print.hdnom.compare.validate

Print model comparison by validation results
validate_external

Externally validate high-dimensional Cox models with time-dependent AUC
summary.hdnom.validate

Summary of validation results
print.hdnom.nomogram

Print nomograms objects
ncvreg_tune_gamma_alpha

Automatic Mnet/Snet gamma and alpha tuning function by k-fold cross-validation
validate

Validate high-dimensional Cox models with time-dependent AUC
smart

Imputed SMART study data
print.hdnom.validate.external

Print external validation results
plot.hdnom.validate

Plot optimism-corrected time-dependent discrimination curves for validation
print.hdnom.calibrate

Print calibration results
print.hdnom.validate

Print validation results
plot.hdnom.validate.external

Plot time-dependent discrimination curves for external validation
summary.hdnom.validate.external

Summary of external validation results
theme_hdnom

Plot theme (ggplot2) for hdnom
summary.hdnom.calibrate.external

Summary of external calibration results
summary.hdnom.compare.calibrate

Summary of model comparison by calibration results
fit_enet

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

Compute Kaplan-Meier estimated survival probabilities for calibration
as_nomogram

Construct nomogram ojects for high-dimensional Cox models
calibrate

Calibrate high-dimensional Cox models
fit_flasso

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

Externally calibrate high-dimensional Cox models
fit_alasso

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

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

Compare high-dimensional Cox models by model validation
compare_by_calibrate

Compare high-dimensional Cox models by model calibration
glmnet_basesurv

Breslow baseline hazard estimator for glmnet objects
glmnet_survcurve

Survival curve prediction for glmnet objects
fit_mcp

Model selection for high-dimensional Cox models with MCP 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
glmnet_calibrate_surv_prob_pred

Compute glmnet predicted survival probabilities for calibration
glmnet_tune_alpha

Automatic alpha tuning function by k-fold cross-validation
glmnet_calibrate_external_surv_prob_pred

Compute glmnet predicted survival probabilities for external calibration
calibrate_external_surv_prob_true

Compute Kaplan-Meier estimated survival probabilities for external calibration