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Publications by De Bin, Riccardo

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Number of items: 16.

Journal article

Volkmann, Alexander; De Bin, Riccardo; Sauerbrei, Willi; Boulesteix, Anne-Laure (2019): A plea for taking all available clinical information into account when assessing the predictive value of omics data. In: BMC Medical Research Methodology 19:162 [PDF, 913kB]

De Bin, Riccardo; Sauerbrei, Willi (2018): Handling co-dependence issues in resampling-based variable selection procedures: a simulation study. In: Journal of Statistical Computation and Simulation, Vol. 88, No. 1: pp. 28-55

De Bin, Riccardo (2016): On the equivalence between conditional and random-effects likelihoods in exponential families. In: Statistics & Probability Letters, Vol. 110: pp. 34-38

De Bin, Riccardo (2016): Boosting in Cox regression: a comparison between the likelihood-based and the model-based approaches with focus on the R-packages CoxBoost and mboost. In: Computational Statistics, Vol. 31, No. 2: pp. 513-531

De Bin, Riccardo; Janitza, Silke; Sauerbrei, W.; Boulesteix, Anne-Laure (2015): Subsampling versus bootstrapping in resampling-based model selection for multivariable regression. In: Biometrics, Vol. 72, No. 1: pp. 272-280

De Bin, Riccardo; Severini, T. A.; Sartori, N. (2015): Integrated likelihoods in models with stratum nuisance parameters. In: Electronic Journal of Statistics, Vol. 9, No. 1: pp. 1474-1491

De Bin, Riccardo; Herold, Tobias; Boulesteix, Anne-Laure (2014): Added predictive value of omics data: specific issues related to validation illustrated by two case studies. In: BMC Medical Research Methodology 14:117 [PDF, 765kB]

Paper

Seibold, Heidi; Bernau, Christoph; Boulesteix, Anne-Laure; De Bin, Riccardo (7. January 2016): On the choice and influence of the number of boosting steps. Department of Statistics: Technical Reports, No.188 [PDF, 472kB]

Boulesteix, Anne-Laure; De Bin, Riccardo; Jiang, Xiaoyu; Fuchs, Mathias (17. December 2015): IPF-LASSO: integrative L1-penalized regression with penalty factors for prediction based on multi-omics data. Department of Statistics: Technical Reports, No.187 [PDF, 497kB]

De Bin, Riccardo (2. April 2015): Boosting in Cox regression: a comparison between the likelihood-based and the model-based approaches with focus on the R-packages CoxBoost and mboost. Department of Statistics: Technical Reports, No.180 [PDF, 507kB]

De Bin, Riccardo; Janitza, Silke; Sauerbrei, Willi; Boulesteix, Anne-Laure (14. October 2014): Subsampling versus bootstrapping in resampling-based model selection for multivariable regression. Department of Statistics: Technical Reports, No.171 [PDF, 379kB]

De Bin, Riccardo; Scarpa, Bruno (8. September 2014): Non-parametric Bayesian modeling of cervical mucus symptom. Department of Statistics: Technical Reports, No.170 [PDF, 460kB]

De Bin, Riccardo; Sartori, Nicola; Severini, Thomas A. (26. February 2014): Integrated likelihoods in models with stratum nuisance parameters. Department of Statistics: Technical Reports, No.157 [PDF, 419kB]

De Bin, Riccardo; Herold, Tobias; Boulesteix, Anne-Laure (18. February 2014): Added predictive value of omics data: specific issues related to validation illustrated by two case studies. Department of Statistics: Technical Reports, No.154 [PDF, 542kB]

Fuchs, Mathias; Hornung, Roman; De Bin, Riccardo; Boulesteix, Anne-Laure (12. November 2013): A U-statistic estimator for the variance of resampling-based error estimators. Department of Statistics: Technical Reports, No.148 [PDF, 323kB]

De Bin, Riccardo; Sauerbrei, Willi; Boulesteix, Anne-Laure (31. October 2013): Investigating the prediction ability of survival models based on both clinical and omics data: two case studies. Department of Statistics: Technical Reports, No.153 [PDF, 453kB]

This list was generated on Sun Sep 15 12:26:21 2019 CEST.