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UID:20251120T221920EST-9994JXXJvP@132.216.98.100
DTSTAMP:20251121T031920Z
DESCRIPTION:Title: SAM: Self-adapting Mixture Prior to Dynamically Borrow I
 nformation from Historical Data in Clinical Trials.\n\nAbstract\n\n \n\nMi
 xture priors provide an intuitive way to incorporate historical data while
  accounting for potential prior-data conflict by combining an informative 
 prior with a non-informative prior. However\, pre-specifying the mixing we
 ight for each component remains a crucial challenge. Ideally\, the mixing 
 weight should reflect the degree of prior-data conflict\, which is often u
 nknown beforehand\, posing a significant obstacle to the application and a
 cceptance of mixture priors. To address this challenge\, we introduce self
 -adapting mixture (SAM) priors that determine the mixing weight using like
 lihood ratio test statistics or Bayes factors. SAM priors are data-driven 
 and self-adapting\, favoring the informative (non-informative) prior compo
 nent when there is little (substantial) evidence of prior-data conflict. C
 onsequently\, SAM priors achieve dynamic information borrowing. We demonst
 rate that SAM priors exhibit desirable properties in both finite and large
  samples and achieve information-borrowing consistency. We developed R pac
 kage 'SAMprior' to facilitate the use of SAM priors.\n	\n	Speaker Bio\n\n\n	Y
 ing Yuan is the Bettyann Asche Murray Distinguished Professor and Chair of
  the Department of Biostatistics at the University of Texas MD Anderson Ca
 ncer Center. Dr. Yuan is internationally renowned for his pioneering resea
 rch in innovative Bayesian adaptive designs\, including early-phase trials
 \, seamless trials\, biomarker-guided trials\, and basket and platform tri
 als. The designs and software developed by Dr. Yuan’s lab (www.trialdesign
 .org) have been widely adopted by medical research institutes and pharmace
 utical companies. Among these\, the BOIN design\, developed by Dr. Yuan’s 
 team\, is a groundbreaking oncology dose-finding method recognized by the 
 FDA as a fit-for-purpose drug development tool. Dr. Yuan is also an electe
 d Fellow of the American Statistical Association and the lead author of tw
 o seminal books: Bayesian Designs for Phase I-II Clinical Trials and Model
 -Assisted Bayesian Designs for Dose Finding and Optimization\, both publis
 hed by Chapman & Hall/CRC.\n
DTSTART:20251120T194500Z
DTEND:20251120T194500Z
LOCATION:Room 1203\, 91ºÚÁÏÍø College 2001\, CA\, QC\, Montreal\, H3A 1G1\, 2
 001\, avenue 91ºÚÁÏÍø College
SUMMARY:Ying Yuan (University of Texas)
URL:/mathstat/channels/event/ying-yuan-university-texa
 s-369117
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