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 |