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TZID:America/New_York
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DTSTART:20241103T020000
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DTSTART:20250309T020000
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DESCRIPTION:Attendance via Zoom. Speaker- Joel Dubin\, Ph.D. Title- Simila
 rity-based statistical modeling Abstract Similarity is a commonly used te
 rm in statistics\, including for purposes of matching study participants 
 or for either unsupervised or supervised learning contexts. In this prese
 ntation\, we will look at some uses of similarity for the aim of improvin
 g predictive model accuracy when utilizing statistical modeling in health
  studies. Thought needs to go into how to define similarity\, including c
 onsideration of an unsupervised or supervised approach\; how to incorpora
 te categorical predictors\; how to utilize weighting\; how to tune simila
 rity\; and how to quantify uncertainty when implementing a similarity ste
 p. Some applications with intensive care unit data will be discussed.\n\n
 Speaker:\nJoel Dubin\, PhD\n\nAdmission:\nFree\n\nDetails URL:\nhttps://m
 edicine.yale.edu/event/ysph-biostatistics-seminar-tbn-21/\n
DTEND;TZID=America/New_York:20220201T130000
DTSTAMP:20261005T162115Z
DTSTART;TZID=America/New_York:20220201T120000
GEO:41.302961;-72.931638
LOCATION:106A\, 47 College Street\, New Haven\, CT\, United States
SEQUENCE:0
STATUS:Confirmed
SUMMARY:YSPH Biostatistics Seminar: "Similarity-based Statistical Modeling"
UID:3d4a9285-4cfe-444d-ba54-a5f691242a74
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