R: Penalized Regression Calibration for the Dynamic Prediction of Survival

# Penalized Regression Calibration for the Dynamic Prediction of Survival

## Documentation for package ‘pencal’ version 2.3.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

fitted_prclmm | A fitted PRC LMM
fitted_prcmlpmm | A fitted PRC MLPMM
fit_lmms | Step 1 of PRC LMM (estimation of the linear mixed models)
fit_mlpmms | Step 1 of PRC MLPMM (estimation of the linear mixed models)
fit_prclmm | Step 3 of PRC LMM (estimation of the penalized Cox model(s))
fit_prcmlpmm | Step 3 of PRC MLPMM (estimation of the penalized Cox model(s))
pbc2data | pbc2 dataset
pencox | Estimation of a penalized Cox model with time-independent covariates
performance_pencox | Predictive performance of the penalized Cox model with time-independent covariates
performance_prc | Predictive performance of the PRC-LMM and PRC-MLPMM models
print.prclmm | Print method for PRC LMM model fits
print.prcmlpmm | Print method for PRC MLPMM model fits
simulate_prclmm_data | Simulate data that can be used to fit the PRC LMM model
simulate_prcmlpmm_data | Simulate data that can be used to fit the PRC MLPMM model
simulate_t_weibull | Generate survival data from a Weibull model
summarize_lmms | Step 2 of PRC LMM (computation of the predicted random effects)
summarize_mlpmms | Step 2 of PRC MLPMM (computation of the predicted random effects)
summary.lmmfit | Extract model fits from step 1 of PRC-LMM
summary.mlpmmfit | Extract model fits from step 1 of PRC-LMM
summary.prclmm | Summary method for PRC LMM model fits
summary.prcmlpmm | Summary method for PRC MLPMM model fits
summary.ranefs | Summary for step 2 of PRC
survplot_prc | Visualize survival predictions for a fitted PRC model
survpred_prclmm | Compute the predicted survival probabilities obtained from the PRC LMM model
survpred_prcmlpmm | Compute the predicted survival probabilities obtained from the PRC MLPMM models