3 papers
stat.ME2026
Smooth Transformation Models for Survival Analysis: A Tutorial Using R
Sandra Siegfried, Bálint Tamási, Torsten Hothorn
Over the last five decades, we have seen strong methodological advances in survival analysis, using parametric methods and, more prominently, methods based on non-/semi-parametric…
stat.ME2025
Likelihood-based Modeling of Covariate-Specific Time-Dependent ROC Curves
Ainesh Sewak, Vanda Inacio, Joanne Wuu +2
Identifying reliable biomarkers for predicting clinical events in longitudinal studies is important for accurate disease prognosis and for guiding development of new treatments. Ho…
stat.ME2025
Transformation Discriminant Analysis for Constructing Optimal Biomarker Combinations
Ainesh Sewak, Sandra Siegfried, Torsten Hothorn
Accurate diagnostic tests are essential for effective screening and treatment. However, individual biomarkers often fail to provide sufficient diagnostic accuracy, as they typicall…