| 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. |
