In many medical applications, data are taken from paired organs or from repeated measurements of the same organ or subject. Subject based as opposed to observation based evaluation of these data results in increased efficiency of the estimation of the misclassification rate. A subject based...

The quest of the best classifier for a discriminant analysis problem is often rather hard and a combination of classifiers of different type promises to lead to improved predictive models compared to selecting one of the competitors. We propose to use the out-of-bag sample for training of...

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic...

Predicted survival probability functions of censored event free survival are improved by bagging survival trees. We suggest a new method to aggregate survival trees in order to obtain better predictions for breast cancer and lymphoma patients.A set of survival trees based on bootstrap samples is...

Diagnosis based on medical image data is common in clinical research and clinical routine. We discuss a strategy to derive a classifier with good performance on clinical image data and to justify the properties of the classifier by an adapted simulation model of image data. As learning set we...