create_folds: Create folds for cross-validation.
In MTLR: Survival Prediction with Multi-Task Logistic Regression

Description Usage Arguments Value See Also

Create the test folds for k-fold cross validation. These cross-validation types differ from typical stratified cross-validation as this function also considers the range of event times in the data.

1 2	create_folds(time, delta, nfolds, foldtype = c("fullstrat", "censorstrat", "random"))

`time`	a vector of event times.
`delta`	a vector of indicators for uncensored/censored data. The type of censoring here is not considered so it is suggested this function not be used for data with mixed censoring types. The specific indicator value does not matter as long as censored and uncensored observations have different values for their indicator.
`nfolds`	The number of folds to create.
`foldtype`	type of cross validation folds. Full stratification, "fullstrat", sorts observations by their event time and their event indicators and numbers them off into folds. This effectively give each fold approximately the same number of uncensored observations as well as keeps the range of time points as equivalent as possible across folds. This type of cross-validation is completely deterministic. Censored stratification, "censorstrat", will put approximately the same number of uncensored observations in each fold but not pay any attention to event time. This is partially stochastic. The totally random cross-validation, "random", randomly assigns observations to folds without considering event time nor event status.