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Jan Beyersmann

Showing results (31-40 of 112) with videos related to

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Biometrical Journal. Biometrische Zeitschrift|October 29, 2025
Non-Markov Nonparametric Estimation of Complex Multistate Outcomes After Hematopoietic Stem Cell TransplantationJudith Vilsmeier, Sandra Schmeller, Daniel Fürst, et al.
Statistics in Medicine|June 5, 2019
Bootstrapping complex time-to-event data without individual patient data, with a view toward time-dependent exposuresTobias Bluhmki, Hein Putter, Arthur Allignol, et al.
American Journal of Epidemiology|September 7, 2010
Incidence densities in a competing events analysisNadine Grambauer, Martin Schumacher, Markus Dettenkofer, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|November 23, 2012
Competing risks and multistate modelsClaudia Schmoor, Martin Schumacher, Jürgen Finke, et al.
Journal of Clinical Epidemiology|July 16, 2008
An easy mathematical proof showed that time-dependent bias inevitably leads to biased effect estimationJan Beyersmann, Petra Gastmeier, Martin Wolkewitz, et al.
Statistics in Medicine|July 20, 2007
A competing risks analysis of bloodstream infection after stem-cell transplantation using subdistribution hazards and cause-specific hazardsJan Beyersmann, Markus Dettenkofer, Hartmut Bertz, et al.
Biometrical Journal. Biometrische Zeitschrift|January 25, 2011
Quantifying the predictive accuracy of time-to-event models in the presence of competing risksRotraut Schoop, Jan Beyersmann, Martin Schumacher, et al.
Statistical Methods in Medical Research|December 30, 2017
Bayesian Phase II optimization for time-to-event data based on historical informationAnja Bertsche, Frank Fleischer, Jan Beyersmann, et al.
BMC Medical Research Methodology|July 18, 2018
Simulation shows undesirable results for competing risks analysis with time-dependent covariates for clinical outcomesInga Poguntke, Martin Schumacher, Jan Beyersmann, et al.
Bioinformatics (Oxford, England)|February 27, 2009
Boosting for high-dimensional time-to-event data with competing risksHarald Binder, Arthur Allignol, Martin Schumacher, et al.
Pageof 12

Showing results (31-40 of 112) with videos related to

Sort By:
Pageof 12
Biometrical Journal. Biometrische Zeitschrift|October 29, 2025
Non-Markov Nonparametric Estimation of Complex Multistate Outcomes After Hematopoietic Stem Cell TransplantationJudith Vilsmeier, Sandra Schmeller, Daniel Fürst, et al.
Statistics in Medicine|June 5, 2019
Bootstrapping complex time-to-event data without individual patient data, with a view toward time-dependent exposuresTobias Bluhmki, Hein Putter, Arthur Allignol, et al.
American Journal of Epidemiology|September 7, 2010
Incidence densities in a competing events analysisNadine Grambauer, Martin Schumacher, Markus Dettenkofer, et al.
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research|November 23, 2012
Competing risks and multistate modelsClaudia Schmoor, Martin Schumacher, Jürgen Finke, et al.
Journal of Clinical Epidemiology|July 16, 2008
An easy mathematical proof showed that time-dependent bias inevitably leads to biased effect estimationJan Beyersmann, Petra Gastmeier, Martin Wolkewitz, et al.
Statistics in Medicine|July 20, 2007
A competing risks analysis of bloodstream infection after stem-cell transplantation using subdistribution hazards and cause-specific hazardsJan Beyersmann, Markus Dettenkofer, Hartmut Bertz, et al.
Biometrical Journal. Biometrische Zeitschrift|January 25, 2011
Quantifying the predictive accuracy of time-to-event models in the presence of competing risksRotraut Schoop, Jan Beyersmann, Martin Schumacher, et al.
Statistical Methods in Medical Research|December 30, 2017
Bayesian Phase II optimization for time-to-event data based on historical informationAnja Bertsche, Frank Fleischer, Jan Beyersmann, et al.
BMC Medical Research Methodology|July 18, 2018
Simulation shows undesirable results for competing risks analysis with time-dependent covariates for clinical outcomesInga Poguntke, Martin Schumacher, Jan Beyersmann, et al.
Bioinformatics (Oxford, England)|February 27, 2009
Boosting for high-dimensional time-to-event data with competing risksHarald Binder, Arthur Allignol, Martin Schumacher, et al.
Pageof 12