R. Hornung

J. Mayerle, R. Hornung, A. Gerbes, 2019, Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver.

Mediation analysis reveals common mechanisms of RUNX1 point mutations and RUNX1/RUNX1T1 fusions influencing survival of patients with acute myeloid leukemia

A. Boulesteix, W. Hiddemann, K. Metzeler, 2018, Scientific Reports.

Improved Outcome Prediction Across Data Sources Through Robust Parameter Tuning

A. Boulesteix, R. Hornung, Bernd Bischl, 2020, Journal of Classification.

Sequential Permutation Testing of Random Forest Variable Importance Measures

R. Hornung, A. Hapfelmeier, Bernhard Haller, 2022, Comput. Stat. Data Anal..

A U-statistic estimator for the variance of resampling-based error estimators

Roman Hornung, Anne-Laure Boulesteix, Riccardo De Bin, 2013, 1310.8203.

Large-scale benchmark study of survival prediction methods using multi-omics data

Moritz Herrmann, Philipp Probst, Roman Hornung, 2020, Briefings Bioinform..

A Diagnostic Model for Kawasaki Disease Based on Immune Cell Characterization From Blood Samples

U. Mansmann, R. Hornung, B. Geisler, 2022, Frontiers in Pediatrics.

On Fishing for Significance and Statistician’s Degree of Freedom in the Era of Big Molecular Data

Roman Hornung, Anne-Laure Boulesteix, Willi Sauerbrei, 2017 .

Synergistic Effects of Different Levels of Genomic Data for the Staging of Lung Adenocarcinoma: An Illustrative Study

U. Mansmann, R. Hornung, Shangming Du, 2021, Genes.

Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment

A. Boulesteix, R. Hornung, D. Causeur, 2016, BMC Bioinformatics.

Prediction approaches for partly missing multi-omics covariate data: A literature review and an empirical comparison study

A. Boulesteix, R. Hornung, Frederik Ludwigs, 2023, ArXiv.

Block Forests: random forests for blocks of clinical and omics covariate data

Roman Hornung, Marvin N. Wright, R. Hornung, 2019, BMC Bioinformatics.

Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data

A. Boulesteix, R. Hornung, T. Herold, 2018, BMC Bioinformatics.

Improving cross‐study prediction through addon batch effect adjustment or addon normalization

David Causeur, Roman Hornung, Anne-Laure Boulesteix, 2016, Bioinform..

Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data

Roman Hornung, Vindi Jurinovic, Anne-Laure Boulesteix, 2018, BMC Bioinformatics.

Mediation analysis reveals common mechanisms of RUNX1 point mutations and RUNX1/RUNX1T1 fusions influencing survival of patients with acute myeloid leukemia

A. Boulesteix, W. Hiddemann, K. Metzeler, 2018, Scientific Reports.

Preparation of high-dimensional biomedical data with a focus on prediction and error estimation

Roman Hornung, R. Hornung, 2016 .

A measure of the impact of CV incompleteness on prediction error estimation with application to PCA and normalization

Rory Wilson, Roman Hornung, Caroline Truntzer, 2015, BMC Medical Research Methodology.

Making complex prediction rules applicable for readers: Current practice in random forest literature and recommendations

Philipp Probst, Roman Hornung, Anne-Laure Boulesteix, 2018, Biometrical journal. Biometrische Zeitschrift.

Combining location-and-scale batch effect adjustment with data cleaning by latent factor adjustment

David Causeur, Roman Hornung, Anne-Laure Boulesteix, 2016, BMC Bioinformatics.

Diversity Forests: Using Split Sampling to Enable Innovative Complex Split Procedures in Random Forests

Roman Hornung, R. Hornung, 2021, SN Computer Science.

Single-center versus multi-center data sets for molecular prognostic modeling: a simulation study

A. Boulesteix, C. Belka, R. Hornung, 2020, Radiation oncology.

Sequential Permutation Testing of Random Forest Variable Importance Measures

A. Hapfelmeier, R. Hornung, B. Haller, 2022, arXiv.org.

Interaction forests: Identifying and exploiting interpretable quantitative and qualitative interaction effects

Roman Hornung, Anne-Laure Boulesteix, A. Boulesteix, 2021, Comput. Stat. Data Anal..

Ordinal Forests

Roman Hornung, R. Hornung, 2020, J. Classif..

Improving Cross-study Prediction through Addon Batch Effect Adjustment and Addon Normalization Improving Cross-study Prediction through Addon Batch Effect Adjustment and Addon Normalization

A. Boulesteix, R. Hornung, C. Bernau, 2022 .

Full versus incomplete cross-validation: measuring the impact of imperfect separation between training and test sets in prediction error estimation

Roman Hornung, Caroline Truntzer, Anne-Laure Boulesteix, 2014 .