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DTSTAMP:20251122T171139Z
DESCRIPTION:The Accelerated Trend-Renewal Process for Recurrent Event Data.
 \n\nChien-Lin (Mark) Su is a postdoctoral fellowship at the department of 
 Mathematics and Statistics\, ɬÀï·¬ under the joint supervision
  of Professors Russell Steele and Johanna Nešlehová. He got his Ph.D. degr
 ee in statistics from Taiwan in 2015 and was awarded the STATLAB-CANSSI-CR
 M postdoc under the joint supervision of Professors Russell Steele (ɬÀï·¬
  University) and Lajmi Lakhal-Chaieb (Université Laval) from September 1st
 \, 2016 to August 31\, 2017. His research interests include multivariate s
 urvival analysis\, copula model applications in biomedical research and ca
 usal inference.\n\n	Recurrent events data arises in many biomedical and lon
 gitudinal studies when failure events can occur repeatedly for each subjec
 t during the follow-up time. In this work\, we are interested in the gap t
 imes between recurrent events. We propose a semiparametric accelerated tra
 nsform gap time model based on trend-renewal process which contains a tren
 d and a renewal component. We use the Buckley-James imputation approach to
  deal with censored transform gap times. The proposed estimators are shown
  to be consistent and asymptotically normal. Model diagnostic plots of res
 iduals and a prediction method for predicting number of recurrent events g
 iven a specified covariate and follow-up time are also presented. Simulati
 on studies are conducted to assess finite sample performances of the propo
 sed method. The proposed technique is demonstrated through an application 
 to two real data sets.\n
DTSTART:20180213T203000Z
DTEND:20180213T213000Z
LOCATION:Room 24\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue
  des Pins Ouest
SUMMARY:Chien-Lin Su (Mark)\, PhD\, Postdoctoral Fellow - ɬÀï·¬
URL:/mathstat/channels/event/chien-lin-su-mark-phd-pos
 tdoctoral-fellow-mcgill-285063
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