as_nomogram | Construct nomogram ojects for high-dimensional Cox models |
calibrate | Calibrate high-dimensional Cox models |
calibrate_external | Externally calibrate high-dimensional Cox models |
compare_by_calibrate | Compare high-dimensional Cox models by model calibration |
compare_by_validate | Compare high-dimensional Cox models by model validation |
fit_aenet | Model selection for high-dimensional Cox models with adaptive elastic-net 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_flasso | Model selection for high-dimensional Cox models with fused lasso penalty |
fit_lasso | Model selection for high-dimensional Cox models with lasso 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_scad | Model selection for high-dimensional Cox models with SCAD penalty |
fit_snet | Model selection for high-dimensional Cox models with Snet penalty |
glmnet_basesurv | Breslow baseline hazard estimator for glmnet objects |
glmnet_survcurve | Survival curve prediction for glmnet objects |
infer_variable_type | Extract information of selected variables from high-dimensional Cox models |
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 |
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 |
plot.hdnom.calibrate | Plot calibration results |
plot.hdnom.calibrate.external | Plot external calibration results |
plot.hdnom.compare.calibrate | Plot model comparison by calibration results |
plot.hdnom.compare.validate | Plot model comparison by validation results |
plot.hdnom.nomogram | Plot nomogram objects |
plot.hdnom.validate | Plot optimism-corrected time-dependent discrimination curves for validation |
plot.hdnom.validate.external | Plot time-dependent discrimination curves for external validation |
predict.hdnom.model | Make predictions from high-dimensional Cox models |
print.hdnom.calibrate | Print calibration results |
print.hdnom.calibrate.external | Print external calibration results |
print.hdnom.compare.calibrate | Print model comparison by calibration results |
print.hdnom.compare.validate | Print model comparison by validation results |
print.hdnom.model | Print high-dimensional Cox model objects |
print.hdnom.nomogram | Print nomograms objects |
print.hdnom.validate | Print validation results |
print.hdnom.validate.external | Print external validation results |
smart | Imputed SMART study data |
smarto | Original SMART study data |
summary.hdnom.calibrate | Summary of calibration results |
summary.hdnom.calibrate.external | Summary of external calibration results |
summary.hdnom.compare.calibrate | Summary of model comparison by calibration results |
summary.hdnom.compare.validate | Summary of model comparison by validation results |
summary.hdnom.validate | Summary of validation results |
summary.hdnom.validate.external | Summary of external validation results |
theme_hdnom | Plot theme (ggplot2) for hdnom |
validate | Validate high-dimensional Cox models with time-dependent AUC |
validate_external | Externally validate high-dimensional Cox models with time-dependent AUC |