I have 1000 observations with 20 events (2%). Splitting them into 10 will get me only 2 events per fold. Splitting the training folds into 10 sub-folds for model building and optimisation will get me even lower event rate.
Is it correct to say that 10-fold cross-validation is not appropriate for these data?
What are the alternatives? Is repeating 2-fold validations 1000 times a better option?