Current Research Information SysTem In Norway
 
 

 English version


 
Hovedside
Forskningsresultater/NVI
Forskere
Prosjekter
Forskningsenheter
Logg inn
Om Cristin
 
 
   
Eksporter til


Viser treff 1-38 av 38

2019
1 Belhechmi, Shaima; De Bin, Riccardo; Michiels, Stefan; Rotolo, Federico.
Prise en compte des groupes de biomarqueurs ou des voies biologiques dans les modèles de Cox pénalisés de haute dimension. Revue d'épidémiologie et de santé publique 2019 ;Volum 67. Suppl. 3
UiO Untitled
 
2 De Bin, Riccardo.
Detection of influential points as a byproduct of resampling-based variable selection procedures. Seminars in Statistics; 2019-02-21 - 2019-02-21
UiO Untitled
 
3 De Bin, Riccardo.
Detection of influential points as a byproduct of resampling-based variable selection procedures. Seminar Series Statistics; 2019-02-04 - 2019-02-04
UiO Untitled
 
4 De Bin, Riccardo.
Strategies to handle mandatory covariates using model- and likelihood-based boosting. Statistical Meeting; 2019-05-08 - 2019-05-08
UiO Untitled
 
5 De Bin, Riccardo.
Strategies to handle mandatory covariates using model- and likelihood-based boosting. Seminar in Statistics; 2019-03-05 - 2019-03-05
UiO Untitled
 
6 Volkmann, Alexander; De Bin, Riccardo; Sauerbrei, Willi; Boulesteix, Anne-Laure.
A plea for taking all available clinical information into account when assessing the predictive value of omics data. BMC Medical Research Methodology 2019 ;Volum 19. s. 162-
UiO Untitled
 
2018
7 De Bin, Riccardo.
Combining low-dimensional clinical and high-dimensional molecular data in a survival prediction model. CMStatistics 2018; 2018-12-14 - 2018-12-16
UiO Untitled
 
8 De Bin, Riccardo.
Integrated likelihoods in the context of distributed computing. Workshop on Distributed Computing, Differential Privacy and Boosting; 2018-11-22 - 2018-11-23
UiO Untitled
 
9 De Bin, Riccardo.
Meta-analysis and selection for significance. Seminar in Biostatistics; 2018-12-18 - 2018-12-18
UiO Untitled
 
10 De Bin, Riccardo.
On combining clinical and omics data in regression prediction models. FocuStat Research Kitchen: Combination of Data Sources; 2018-11-12 - 2018-11-14
UiO Untitled
 
11 De Bin, Riccardo.
On the equivalence between conditional and random-effects likelihoods in exponential families. The 27th Nordic Conference in Mathematical Statistics; 2018-06-26 - 2018-06-29
UiO Untitled
 
12 De Bin, Riccardo.
Strategies to derive combined prediction models using both clinical predictors and high-throughput molecular data. FocuStat Conference: Vårens Vakreste Variabler; 2018-05-22 - 2018-05-25
UiO Untitled
 
13 De Bin, Riccardo.
Strategies to derive combined prediction models using both clinical predictors and high-throughput molecular data. 1 st Workshop of Topic group 9 High-dimensional data (TG9) of the STRATOS initiative; 2018-03-20 - 2018-03-23
UiO Untitled
 
14 De Bin, Riccardo.
Strategies to derive combined prediction models using both clinical predictors and high-throughput molecular data. Seminar Series in Biostatistics; 2018-11-01 - 2018-11-01
UiO Untitled
 
15 De Bin, Riccardo.
Strategies to handle mandatory covariates using model- and likelihood-based boosting. Seminar Series in Statistics; 2018-12-17 - 2018-12-17
UiO Untitled
 
16 De Bin, Riccardo; Sauerbrei, Willi.
Handling co-dependence issues in resampling-based variable selection procedures: a simulation study. Journal of Statistical Computation and Simulation 2018 ;Volum 88.(1) s. 28-55
UiO Untitled
 
17 Fuchs, Mathias; Hornung, Roman; Boulesteix, Anne-Laure; De Bin, Riccardo.
An asymptotic test for the equality of error rates based on variance estimation of complete subsampling. XXIXth International Biometric Conference; 2018-07-03 - 2018-07-13
UiO Untitled
 
18 van Gruting, Isabelle; Kluivers, Kirsten B; Sultan, Abdul H.; De Bin, Riccardo; Stankiewicz, Aleksandra; Blake, H.; Thakar, Ranee.
Has 4D transperineal ultrasound additional value over 2D transperineal ultrasound for diagnosing obstructed defaecation syndrome?. Ultrasound in Obstetrics and Gynecology 2018
Untitled
 
2017
19 Boulesteix, Anne-Laure; De Bin, Riccardo; Jiang, Xiaoyu; Fuchs, Mathias.
IPF-LASSO: Integrative L1-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data. Computational & Mathematical Methods in Medicine 2017 ;Volum 2017. s. -
UiO Untitled
 
20 De Bin, Riccardo.
Detection of influential points as a byproduct of resampling-based variable selection procedures. CFE-CMStatistics 2017; 2017-12-16 - 2017-12-18
UiO Untitled
 
21 De Bin, Riccardo.
Extensions of threshold-hitting models to higher dimension. FocuStat Research Kitchen: From Processes to Models; 2017-11-15 - 2017-11-17
UiO Untitled
 
22 De Bin, Riccardo.
Integrated likelihoods in the presence of many nuisance parameters. Det 19. norske statistikermøtet; 2017-06-12 - 2017-06-15
UiO Untitled
 
23 De Bin, Riccardo.
Integrated likelihoods in the presence of many nuisance parameters. International FocuStat Workshop: Bridging Parametrics and Nonparametrics; 2017-05-22 - 2017-05-24
UiO Untitled
 
24 De Bin, Riccardo.
Overview of Topics Related to Model Selection for Regression. Trends in Mathematics 2017 ;Volum 7. s. 77-82
Untitled
 
25 De Bin, Riccardo.
Strategies to handle mandatory covariates using model- and likelihood-based boosting. Seminars at the Department of Medical Information, Biometry and Epidemiology of the LMU; 2017-03-14 - 2017-03-14
UiO Untitled
 
26 De Bin, Riccardo.
Strategies to handle mandatory covariates using model- and likelihood-based boosting. The research seminars of the Gustave Roussy Deparment of Biostatistics; 2017-05-29 - 2017-05-29
UiO Untitled
 
27 De Bin, Riccardo.
Strategies to handle mandatory covariates using model- and likelihood-based boosting. Nordic-Baltic Biometric Conference 2017; 2017-06-19 - 2017-06-21
UiO Untitled
 
28 De Bin, Riccardo; Boulesteix, Anne-Laure; Sauerbrei, Willi.
Detection of influential points as a byproduct of resampling-based variable selection procedures. Computational Statistics & Data Analysis 2017 ;Volum 116. s. 19-31
UiO Untitled
 
29 Seibold, Heidi; Bernau, Christoph; Boulesteix, Anne-Laure; De Bin, Riccardo.
On the choice and influence of the number of boosting steps for high-dimensional linear Cox-models. Computational statistics (Zeitschrift) 2017 s. 1195-1215
UiO Untitled
 
30 van Gruting, Isabelle; Stankiewicz, Aleksandra; Kluivers, Kirsten B; De Bin, Riccardo; Blake, Helena; Sultan, Abdul H.; Thakar, Ranee.
Accuracy of Four Imaging Techniques for Diagnosis of Posterior Pelvic Floor Disorders. Obstetrics and Gynecology 2017 ;Volum 130.(5) s. 1017-1024
Untitled
 
2016
31 De Bin, Riccardo.
A note on the equivalence between conditional and random-effects likelihoods in exponential families. Statistics and Probability Letters 2016 ;Volum 110. s. 34-38
Untitled
 
32 De Bin, Riccardo.
Boosting in Cox regression: a comparison between the likelihood-based and the model-based approaches with focus on the R-packages CoxBoost and mboost. Computational statistics (Zeitschrift) 2016 ;Volum 31. s. 513-531
Untitled
 
33 De Bin, Riccardo.
Referee Report For: Three general concepts to improve risk prediction: good data, wisdom of the crowd, recalibration [version 1; referees: 2 approved with reservations]. F1000 Research 2016 ;Volum 5. s. 2671-
UiO Untitled
 
34 De Bin, Riccardo; Janitza, Silke; Sauerbrei, Willi; Boulesteix, Anne-Laure.
Subsampling versus bootstrap in resampling-based model selection for multivariable regression. Biometrics 2016 ;Volum 72.(1) s. 272-280
Untitled
 
2015
35 De Bin, Riccardo; Severini, Thomas A.; Sartori, Nicola.
Integrated likelihoods in models with stratum nuisance parameters. Electronic Journal of Statistics 2015 ;Volum 7. s. 1474-1491
UiO Untitled
 
2014
36 De Bin, Riccardo; Herold, Tobias; Boulesteix, Anne-Laure.
Added predictive value of omics data: specific issues related to validation illustrated by two case studies. BMC Medical Research Methodology 2014 ;Volum 14. s. 117-
Untitled
 
37 De Bin, Riccardo; Sauerbrei, Willi; Boulesteix, Anne-Laure.
Investigating the prediction ability of survival models based on both clinical and omics data: two case studies. Statistics in Medicine 2014 ;Volum 33. s. 5310-5329
Untitled
 
2011
38 De Bin, Riccardo; Risso, Davide.
A novel approach to the clustering of microarray data via nonparametric density estimation.. BMC Bioinformatics 2011 ;Volum 12. s. 49-
Untitled