S4 class for performing a landmarking analysis

Slots

landmarks: A numeric vector of landmark times.
data_static: A data frame containing subject ids, static covariates,
data_dynamic: Data frame in long format with subject ids, measurement values, measurement times and measurement name.
event_indicator: Name of the column indicating event or censoring.
ids: Name of the column indicating subject ids.
times: Name of the column indicating observation time in data_dynamic.
measurements: Name of the column indicating measurement values in data_dynamic.
event_time: Name of the column indicating time of the event/censoring.
risk_sets: List of indices.
longitudinal_fits: List of model fits for the specified landmark times and biomarkers.
longitudinal_predictions: List of model predictions for the specified landmark times and biomarkers.
longitudinal_predictions_test: List of out-of-sample predictions for the specified landmark times and biomarkers.
survival_datasets: List of survival dataframes used in the survival submodel.
survival_datasets_test: List of survival dataframes used for out-of-sample predictions with the survival submodel.
survival_fits: List of survival model fits at each of the specified landmark times.
survival_predictions: List of time-to-event predictions for the specified landmark times and prediction horizons.
survival_predictions_test: List of out-of-sample predictions for the time-to-event outcome if K > 1.
K: Number of cross-validation folds (1 by default)
cv_folds: Data frame associating individuals to cross-validation folds