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DESCRIPTION:Estimation of the Median Residual Lifetime Function for Length-
 Biased Failure Time Data\n\n\n	Abstract:\n\n\nThe median residual lifetime 
 function is a statistical quantity which describes the future point in tim
 e at which the probability of current survival has dropped by 50%. In deri
 ving an estimator for the median residual lifetime function for length-bia
 sed data\, the added features of left-truncation and right-censoring must 
 be taken into account.\n\nIn this talk\, we give a brief description of le
 ngth-biased failure time data and show that by using a particular non-para
 metric estimator for the survival function that it is possible to derive t
 he asymptotically most-efficient non-parametric estimator for the median r
 esidual lifetime function. We give some details on the proof of the asympt
 otic results and examine the performance of the estimator using simulated 
 data. We also apply the proposed estimator to the Canadian Study of Health
  and Aging data set to study the median residual lifetime function of pati
 ents with dementia.\n\nThis is joint work with Professor Masoud Asgharian.
 \n\n\n	Speaker\n\n\nJames Hugh McVittie is a PhD student of the Department 
 of Mathematics and Statistics at 9IÖÆ×÷³§Ãâ·Ñ.\n
DTSTART:20181116T203000Z
DTEND:20181116T213000Z
LOCATION:Room 1104\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:James Hugh McVittie 
URL:/mathstat/channels/event/james-hugh-mcvittie-29160
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