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DTSTAMP:20260206T225544Z
DESCRIPTION:Arthur Chatton\, PhD\n\nAssistant Professor of Biostatistics\n	S
 chool of Public Health - Université de Montréal \n\nWHEN: Wednesday\, Febr
 uary 11\, 2026\, from 3:30 to 4:30 p.m.\n	WHERE: Hybrid | 2001 ɬÀï·¬ Colle
 ge Avenue\, Rm 1140\; Zoom\n	NOTE: Arthur Chatton will be presenting in-per
 son at SPGH \n\nAbstract\n\nThe positivity assumption\, meaning all indivi
 duals can receive each treatment modality\, is fundamental in causal infer
 ence. However\, its empirical verification is often overlooked\, presumabl
 y because of its difficulty. After discussing the different types of viola
 tions that may occur\, this talk will show how to go beyond propensity sco
 re to verify this assumption using the Positivity Regression Trees (PoRT) 
 algorithm available in the R library port. Their advantages and disadvanta
 ges will be discussed\, along with potential solutions in the case of a vi
 olation. If time permits\, an extension to the longitudinal and mediation 
 context will be briefly discussed.\n\nSpeaker Bio\n\nArthur Chatton is an 
 Assistant Professor of Biostatistics at the University of Montreal School 
 of Public Health. His works are at the crossroad of prediction and causati
 on\, with an emphasis on the use of super learning approaches. He aims to 
 (i) evaluate and improve the quality\, usability and generalizability of p
 redictive scores for personalizing medical care and (ii) develop and evalu
 ate new causal methods that consider the imperfection of data collected an
 d used for applied research purposes. For more information\, please visit:
  https://arthurchatton.netlify.app/ \n
DTSTART:20260211T203000Z
DTEND:20260211T213000Z
SUMMARY:Checking the Positivity Assumption in Practice
URL:/epi-biostat-occh/channels/event/checking-positivi
 ty-assumption-practice-370611
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