Jan Beyersmann

Summary

Affiliation: University of Freiburg
Country: Germany

Publications

  1. ncbi Transmission-associated nosocomial infections: prolongation of intensive care unit stay and risk factor analysis using multistate models
    Jan Beyersmann
    Institute of Medical Biometry and Medical Informatics, University Medical Center, and Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Freiburg, Germany
    Am J Infect Control 36:98-103. 2008
  2. ncbi An easy mathematical proof showed that time-dependent bias inevitably leads to biased effect estimation
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, Freiburg University, Freiburg, Germany
    J Clin Epidemiol 61:1216-21. 2008
  3. ncbi Nosocomial infection, length of stay, and time-dependent bias
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Germany
    Infect Control Hosp Epidemiol 30:273-6. 2009
  4. ncbi Simulating competing risks data in survival analysis
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Eckerstrasse 1, 79104 Freiburg, Germany
    Stat Med 28:956-71. 2009
  5. ncbi The impact of time-dependent bias in proportional hazards modelling
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Eckerstrasse 1, 79104 Freiburg, Germany
    Stat Med 27:6439-54. 2008
  6. ncbi A random time interval approach for analysing the impact of a possible intermediate event on a terminal event
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, Eckerstrasse 1, D 79104 Freiburg, Germany
    Biom J 49:742-9. 2007
  7. ncbi Risk factors for the development of nosocomial pneumonia and mortality on intensive care units: application of competing risks models
    Martin Wolkewitz
    Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany
    Crit Care 12:R44. 2008
  8. ncbi Incidence densities in a competing events analysis
    Nadine Grambauer
    Department of Medical Biometry and Statistics, Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Germany
    Am J Epidemiol 172:1077-84. 2010
  9. ncbi Time-dependent study entries and exposures in cohort studies can easily be sources of different and avoidable types of bias
    Martin Wolkewitz
    Institute of Medical Biometry and Medical Informatics, University of Freiburg, Freiburg, Germany
    J Clin Epidemiol 65:1171-80. 2012
  10. ncbi Time-dependent covariates in the proportional subdistribution hazards model for competing risks
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Freiburg, Germany
    Biostatistics 9:765-76. 2008

Detail Information

Publications22

  1. ncbi Transmission-associated nosocomial infections: prolongation of intensive care unit stay and risk factor analysis using multistate models
    Jan Beyersmann
    Institute of Medical Biometry and Medical Informatics, University Medical Center, and Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Freiburg, Germany
    Am J Infect Control 36:98-103. 2008
    ..We investigated the prolongation of intensive care unit (ICU) length of stay (LOS) because of transmission-associated NI (TANI) in a prospective study on 5 ICUs with normal NI rates over an 18-month period...
  2. ncbi An easy mathematical proof showed that time-dependent bias inevitably leads to biased effect estimation
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, Freiburg University, Freiburg, Germany
    J Clin Epidemiol 61:1216-21. 2008
    ..As this bias is common, we sought to determine whether it always leads to biased effect estimation. We also sought to determine the direction of the effect bias...
  3. ncbi Nosocomial infection, length of stay, and time-dependent bias
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Germany
    Infect Control Hosp Epidemiol 30:273-6. 2009
    ..Any statistical analysis that does not explicitly model this time dependency will be biased. The bias is not redeemed by adjusting for baseline information...
  4. ncbi Simulating competing risks data in survival analysis
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Eckerstrasse 1, 79104 Freiburg, Germany
    Stat Med 28:956-71. 2009
    ..The simulation illustrates that results from a misspecified proportional subdistribution hazard analysis can be interpreted as a time-averaged effect on the cumulative event probability scale...
  5. ncbi The impact of time-dependent bias in proportional hazards modelling
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Eckerstrasse 1, 79104 Freiburg, Germany
    Stat Med 27:6439-54. 2008
    ..We illustrate our results with data on hospital infection status and different censoring patterns...
  6. ncbi A random time interval approach for analysing the impact of a possible intermediate event on a terminal event
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, Eckerstrasse 1, D 79104 Freiburg, Germany
    Biom J 49:742-9. 2007
    ..We illustrate this by analysing change in length of hospital stay following an infection and derive the large sample properties of the respective estimator...
  7. ncbi Risk factors for the development of nosocomial pneumonia and mortality on intensive care units: application of competing risks models
    Martin Wolkewitz
    Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany
    Crit Care 12:R44. 2008
    ..However, the evaluation in most of theses studies disregards the fact that there are additional competing events, such as discharge or death...
  8. ncbi Incidence densities in a competing events analysis
    Nadine Grambauer
    Department of Medical Biometry and Statistics, Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Germany
    Am J Epidemiol 172:1077-84. 2010
    ..Competing events and even more complex event patterns may be adequately addressed with the suggested methodology...
  9. ncbi Time-dependent study entries and exposures in cohort studies can easily be sources of different and avoidable types of bias
    Martin Wolkewitz
    Institute of Medical Biometry and Medical Informatics, University of Freiburg, Freiburg, Germany
    J Clin Epidemiol 65:1171-80. 2012
    ..To display and discuss the reasons and consequences of length and time-dependent bias. They might occur in presence of a time-dependent study entry or a time-dependent exposure which might change from unexposed to exposed...
  10. ncbi Time-dependent covariates in the proportional subdistribution hazards model for competing risks
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Freiburg, Germany
    Biostatistics 9:765-76. 2008
    ..We illustrate this with hospital infection data, where time-dependent covariates and competing risks are essential to the subject research question...
  11. ncbi Understanding competing risks: a simulation point of view
    Arthur Allignol
    Freiburg Center for Data Analysis and Modeling, University of Freiburg, Germany
    BMC Med Res Methodol 11:86. 2011
    ..A key feature of competing risks is that there are as many hazards as there are competing risks. This is not always well accounted for in the applied literature...
  12. ncbi Nonparametric inference for the cumulative incidence function of a competing risk, with an emphasis on confidence bands in the presence of left-truncation
    Susanna Di Termini
    Freiburg Centre for Data Analysis and Modeling, University of Freiburg, Eckerstraße 1, 79104 Freiburg, Germany
    Biom J 54:568-78. 2012
    ..Simulation results and a real data example are provided...
  13. ncbi Modeling the effect of time-dependent exposure on intensive care unit mortality
    Martin Wolkewitz
    Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Stefan Meier Strasse 26, 79104 Freiburg, Germany
    Intensive Care Med 35:826-32. 2009
    ..To illustrate modern survival models with focus on the temporal dynamics of intensive care data. A typical situation is given in which time-dependent exposures and competing events are present...
  14. ncbi Application of multistate models in hospital epidemiology: advances and challenges
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Eckerstraße 1, Freiburg, Germany
    Biom J 53:332-50. 2011
    ..This overview discusses where survival techniques provide additional insight into hospital epidemiology, and where they are, in fact, needed even in the absence of right-censoring...
  15. ncbi A note on variance estimation of the Aalen-Johansen estimator of the cumulative incidence function in competing risks, with a view towards left-truncated data
    Arthur Allignol
    Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstrasse 1, Freiburg, Germany
    Biom J 52:126-37. 2010
    ..Multistate-type software and data are available online to perform the analyses. The Greenwood-type estimator is recommended for use in practice...
  16. ncbi Quantifying the predictive accuracy of time-to-event models in the presence of competing risks
    Rotraut Schoop
    Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr 1, D 79104 Freiburg, Germany
    Biom J 53:88-112. 2011
    ..A simulation study investigating the behaviour of the estimator in small sample size situations and for different levels of censoring together with a real data application follows...
  17. ncbi Proportional subdistribution hazards modeling offers a summary analysis, even if misspecified
    Nadine Grambauer
    Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstrasse 1, 79104 Freiburg, Germany
    Stat Med 29:875-84. 2010
    ..We reanalyze an interpretationally challenging example from the ONKO-KISS study and conduct a simulation study, where we find that the LFP is reliably estimated by the subdistribution analysis even for moderate sample sizes...
  18. ncbi Development and mechanism of fluoroquinolone resistance in Legionella pneumophila
    Daniel Jonas
    Institute of Environmental Medicine and Hospital of Epidemiology, University Hospital of Freiburg, Hugstetter Strasse 55, D 79106 Freiburg
    J Antimicrob Chemother 51:275-80. 2003
    ..In conclusion, different quinolones lose their antimicrobial effect after a varying number of passages. This study demonstrated, for the first time to our knowledge, that gyrA in L. pneumophila is a possible target of fluoroquinolones...
  19. ncbi A competing risks analysis of bloodstream infection after stem-cell transplantation using subdistribution hazards and cause-specific hazards
    Jan Beyersmann
    Freiburg Centre for Data Analysis and Modelling, University of Freiburg, Eckerstrasse 1, 79104 Freiburg, Germany
    Stat Med 26:5360-9. 2007
    ..Proportional subdistribution hazards modelling of the subdistribution of the CIF is establishing itself as an interpretation-friendly alternative. We apply both methods and discuss their relative merits...
  20. ncbi Boosting for high-dimensional time-to-event data with competing risks
    Harald Binder
    Freiburg Center for Data Analysis and Modeling, University of Freiburg, Eckerstr 1 and Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Freiburg, Germany
    Bioinformatics 25:890-6. 2009
    ..In addition, tools for judging the prediction performance of fitted models have to be provided...
  21. ncbi Competing risks and multistate models
    Claudia Schmoor
    Clinical Trials Unit, University Medical Center Freiburg, Freiburg, Germany
    Clin Cancer Res 19:12-21. 2013
    ..The aim of this nontechnical report is to explain use and interpretation of Cox-type regression models suitable for the different situations in a randomized trial on the effects of anti-T-cell globulin as GVHD prophylaxis...
  22. ncbi Misspecified regression model for the subdistribution hazard of a competing risk
    Jan Beyersmann
    Stat Med 26:1649-51. 2007