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Jan Beyersmann

Statistiker

Name	Jan Beyersmann
Time	2012- (Wirkungsdaten)
Place	Deutschland
Academic degree	Prof. Dr.
Profession	Statistiker (characteristic profession)
Related	Universität Ulm
Further information	Fachgebiet: Biostatistik
Source	Internet: http://www.uni-ulm.de/mawi/statistics/team/prof-dr-jan-beyersmann.html
Record type	Person
GND-Identifier	1053189710
Record ID	1053189710
Involved in show all Outcomes of haploidentical transplants with PT-CY versus 10/10 MUD transplants with ATG in Germany Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): summary of findings and assessment of existing guidelines Design aspects of COVID‐19 treatment trials: Improving probability and time of favorable events Design aspects of COVID‐19 treatment trials: Improving probability and time of favorable events Estimating and comparing adverse event probabilities in the presence of varying follow‐up times and competing events Estimating and comparing adverse event probabilities in the presence of varying follow‐up times and competing events Psychosocial Risk and Health Behaviors as Predictors of Clinical Events in Patients Wait-Listed for a New Heart: Results from 7 Years of Follow-Up Sampling designs for rare time-dependent exposures: a comparison of the nested exposure case-control design and exposure density sampling Sampling designs for rare time-dependent exposures: a comparison of the nested exposure case-control design and exposure density sampling Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) - estimation of adverse event risks Survival analysis for AdVerse events with VarYing follow‐up times (SAVVY): rationale and statistical concept of a meta‐analytic study Survival analysis for AdVerse events with VarYing follow‐up times (SAVVY): Rationale and statistical concept of a meta‐analytic study Statistical models for complex data in clinical and epidemiological research Five years’ trajectories of functionality and pain in patients after hip or knee replacement and association with long‑term patient survival Statistical models for complex data in clinical and epidemiological research Estimands to quantify prolonged hospital stay associated with nosocomial infections Estimands to quantify prolonged hospital stay associated with nosocomial infections On estimands and the analysis of adverse events in the presence of varying follow‐up times within the benefit assessment of therapies Competing-risk outcomes after hematopoietic stem cell transplantation from the perspective of time-dependent effects Optimizing the design and analysis of clinical trials for antibacterials against multidrug-resistant organisms: a white paper from COMBACTE’s STAT-Net Simulation showed undesirable results for competing risk analysis with time-dependent covariates for clinical outcomes On change in length of stay associated with an intermediate event : estimation within multi-state models and large sample properties

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Jan Beyersmann

Outcomes of haploidentical transplants with PT-CY versus 10/10 MUD transplants with ATG in Germany

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): summary of findings and assessment of existing guidelines

Design aspects of COVID‐19 treatment trials: Improving probability and time of favorable events

Design aspects of COVID‐19 treatment trials: Improving probability and time of favorable events

Estimating and comparing adverse event probabilities in the presence of varying follow‐up times and competing events

Estimating and comparing adverse event probabilities in the presence of varying follow‐up times and competing events

Psychosocial Risk and Health Behaviors as Predictors of Clinical Events in Patients Wait-Listed for a New Heart: Results from 7 Years of Follow-Up

Sampling designs for rare time-dependent exposures: a comparison of the nested exposure case-control design and exposure density sampling

Sampling designs for rare time-dependent exposures: a comparison of the nested exposure case-control design and exposure density sampling

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) - estimation of adverse event risks

Survival analysis for AdVerse events with VarYing follow‐up times (SAVVY): rationale and statistical concept of a meta‐analytic study

Survival analysis for AdVerse events with VarYing follow‐up times (SAVVY): Rationale and statistical concept of a meta‐analytic study

Statistical models for complex data in clinical and epidemiological research

Five years’ trajectories of functionality and pain in patients after hip or knee replacement and association with long‑term patient survival

Statistical models for complex data in clinical and epidemiological research

Estimands to quantify prolonged hospital stay associated with nosocomial infections

Estimands to quantify prolonged hospital stay associated with nosocomial infections

On estimands and the analysis of adverse events in the presence of varying follow‐up times within the benefit assessment of therapies

Competing-risk outcomes after hematopoietic stem cell transplantation from the perspective of time-dependent effects

Optimizing the design and analysis of clinical trials for antibacterials against multidrug-resistant organisms: a white paper from COMBACTE’s STAT-Net

Simulation showed undesirable results for competing risk analysis with time-dependent covariates for clinical outcomes

On change in length of stay associated with an intermediate event : estimation within multi-state models and large sample properties