Functions and Utilities for fitting Piece-wise Exponential (Additive) models

add_hazard | Add predicted hazard to data set |

add_survprob | Add survival probability estimates to data set |

add_term | Add info about term effects to data set |

as_fped | Transform data with one row per subject to functional PED... |

as_matdf | Transform a nested data frame to data frame with matrix... |

as_ped | Function to check if an object is of class 'ped' or transform... |

calc_ci | Calculate confidence intervals |

combine_cut | Extract unique cut points when time-dependent covariates... |

combine_df | Combines multiple data frames |

create_Lmat | creates one instance of Lag/Lead mat |

dplyr_verbs | 'dplyr' Verbs for 'ped'-Objects |

extract_one | Exctract id with most observations from fped object |

formula_helpers | Extract variables from the left-hand-side of a formula |

get_cumhazard | Calculate cumulative hazard |

get_grpvars | Extract character vector of grouping variables |

get_hazard | Calculate predicted hazard |

get_intervals | Information on intervals in which times fall |

get_plotinfo | Extract plot information for all special model terms |

get_survprob | Calculate survival probabilities |

get_tdc | Extract time-dependent covariates from data set |

get_term | Extract partial effects for specified model terms |

get_terms | Extract the partial effects of non-linear model terms |

gg_fixed | Forrest plot of fixed coefficients |

gg_re | Plot Normal QQ plots for random effects |

gg_smooth | Plot smooth 1d terms of gam objects |

gg_tensor | Plot tensor product effects |

int_info | Create start/end times and interval information |

int_info2 | Given interval break-points, provides data frame with... |

Lmat | Extend instance of Lag-Lead matrix to whole data set |

Lsimp | Create one instance of the Lag-Lead matrix |

make_X | Construct full data set with time-dependent covariate (TDC) |

modus | Calculate the modus |

newdata | Construct a data frame suitable for prediction |

pamm | Fit a piece-wise exponential additive model |

pamm_package | pamm: Piece-wise exponential Additive Mixed Models |

pec_cv | k-fold cross validated prediction error curve (pec) |

pec_pamm | Fit PAM to train data and calculate PEC on test data |

ped_info | Extract interval information and median/modus values for... |

plot_df | Extract information for plotting step functions |

predictSurvProb.pamm | Predict survival probabilities at specified time points |

riskset_info | Extract risk set information for each interval. |

rm_grpvars | Return ungrouped data frame without grouping variables |

sample_info | Extract information of the sample contained in a data set |

sim_wce | Simulate survival data using the piece-wise exponential... |

split_data | Function to transform data without time-dependent covariates... |

split_tdc | Create piece-wise exponential data in case of time-dependent... |

tidiers | Extract 1d smooth objects in tidy data format. |

tidy_fixed | Extract fixed coefficient table from model object |

tidy_pec | Tranform data from pec object to tidy format |

tidyr_verbs | 'tidyr' Verbs for 'ped'-Objects |

tidy_smooth | Extract random effects objects in tidy data format. |

tidy_smooth2d | Extract 2d smooth objects in tidy format. |

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