Statistical Methods in Organ Failure and Transplantation

Statistical Methods in Organ Failure and Transplantation Stat Biosci (2017) 9:317–319 EDITORIAL Statistical Methods in Organ Failure and Transplantation Douglas E. Schaubel Published online: 27 November 2017 © International Chinese Statistical Association 2017 The special issue contains ten stimulating articles which feature the development of novel statistical methodology applied to important issues in organ failure and trans- plantation. Several of the articles feature survival analysis, which has a long history in the organ failure setting, dating back to (at least) the seminal analysis of the Stanford heart transplant data by Crowley and Hu [1]. Fields such as end-stage renal disease (ESRD) and end-stage liver disease (ESLD) are among the many areas of medicine which have been particularly receptive to (and, as a result, heavily influenced by) innovative statistical techniques. This issue spans several domains with respect to statistical methodology and areas of application, including instrumental variables, competing risks, recurrent events, gap times, landmark analysis, dynamic prediction of outcomes, joint modeling of longitudinal and time-to-event data, and variable selection. Methodologists and prac- titioners whose area of application is outside the organ failure setting will find plenty of stimulating material in this issue. Lehmann et al. [2] propose a weighting approach for instrumental variable (IV) analysis, designed Statistics in Biosciences Springer Journals

Statistical Methods in Organ Failure and Transplantation

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Copyright © 2017 by International Chinese Statistical Association
Statistics; Statistics for Life Sciences, Medicine, Health Sciences; Biostatistics; Theoretical Ecology/Statistics
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