Penalized Regression Calibration (PRC)
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Documentation for package ‘pencal’ version 1.3.2
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| 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)) |
| getlmm | Extract model fits from step 1 of PRC-LMM |
| getmlpmm | Extract model fits from step 1 of PRC-LMM |
| pencox_baseline | Estimation of a penalized Cox model with baseline covariates onlu |
| performance_pencox_baseline | Predictive performance of the penalized Cox model with baseline 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-LMM 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.prclmm | Summary method for PRC-LMM model fits |
| summary.prcmlpmm | Summary method for PRC-MLPMM model fits |
| survpred_prclmm | Compute the predicted survival probabilities obtained from the PRC models |
| survpred_prcmlpmm | Compute the predicted survival probabilities obtained from the PRC models |