Computes a reference models for survival analysis. This is most 
    usefull in (multi-)omics contexts. The reference is a model with 
    clinical-variables only. 
    The clinical-only model can be fit as a standard coxph model 
    (survival::coxph) or with regularisation via lasso or ridge 
    regression (glmnet::cv.glmnet).
    It is required to provide a vector of indices in the 'clinicals' 
    argument, indicating the position of clinical variables in the 
    feature matrix.

Argument of: survival::coxph

logical value: if TRUE, the model frame is returned in component model.

Fraction of all pairs of subjects whose predicted survival times are correctly ordered among all subjects that can actually be ordered. In other words, it is the probability of concordance between the predicted and the observed survival. Corrected by weighting with IPCW as suggested by Uno. Implemented in survAUC::UnoC.

Integrated brier score using Kaplan-Meier estimator for weighting

Only works for methods for which probabilities are provided via pec::predictSurvProb. Currently these are only coxph and randomForestSRC. To set an upper time limit, set argument max.time (defaults to max time in test data). Implemented in pec::pec

Amount of features of feature group 'clin' used for the model

Useful for feature selection. The feature group is specified via extra.arg.
    The names of the features within the group must contain that string. Make sure names of
    features of other groups do not contain this string.

Amount of features of feature group 'cnv' used for the model

Amount of features of feature group 'mirna' used for the model

Amount of features of feature group 'mutation' used for the model

Amount of features of feature group 'rna' used for the model