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UID:20250918T094622EDT-5260momuXm@132.216.98.100
DTSTAMP:20250918T134622Z
DESCRIPTION:Abstract:\n\nIn prevalent cohort studies with follow-up\, the t
 ime-to-event outcome is subject to left truncation leading to selection bi
 as. For estimation of the distribution of time-to-event\, conventional met
 hods adjusting for left truncation tend to rely on the (quasi-)independenc
 e assumption that the truncation time and the event time are “independent'
  on the observed region. This assumption is violated when there is depende
 nce between the truncation time and the event time possibly induced by mea
 sured covariates. Inverse probability of truncation weighting leveraging c
 ovariate information can be used in this case\, but it is sensitive to mis
 specification of the truncation model. In this work\, we apply the semipar
 ametric theory to find the efficient influence curve of an expected (arbit
 rarily transformed) survival time in the presence of covariate-induced dep
 endent left truncation. We then use it to construct estimators that are sh
 own to enjoy double-robustness properties. Our work represents the first a
 ttempt to construct doubly robust estimators in the presence of left trunc
 ation\, which does not fall under the established framework of coarsened d
 ata where doubly robust approaches are developed. We provide technical con
 ditions for the asymptotic properties that appear to not have been careful
 ly examined in the literature for time-to-event data\, and study the estim
 ators via extensive simulation. We apply the estimators to two data sets f
 rom practice\, with different right-censoring patterns.\n\nSpeaker\n\nYuya
 o Wang is a 5th-year PhD student in mathematics with a specialization in s
 tatistics at University of California San Diego. Before entering graduate 
 school\, Yuyao earned her Bachelor’s degree in mathematics at Xi’an Jiaoto
 ng University in China. Yuyao’s research interests include survival analys
 is\, causal inference\, missing data problems\, and semiparametric theory.
  She is also generally interested in health data and aging studies.\n\nhtt
 ps://mcgill.zoom.us/j/84195498572\n\nMeeting ID: 841 9549 8572\n\nPasscode
 : None\n
DTSTART:20231027T193000Z
DTEND:20231027T203000Z
LOCATION:Room 1104\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Yuyao Wang (The University of California San Diego)
URL:/mathstat/channels/event/yuyao-wang-university-cal
 ifornia-san-diego-352169
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