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TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:STANDARD
DTSTART:20241103T020000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
TZOFFSETFROM:-0400
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DTSTART:20250309T020000
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BEGIN:VEVENT
DESCRIPTION:NOTE: BIS 525 students are required to attend in person (47 Co
 llege St.\, Room 106A). All others are requested to attend via Zoom. SPEA
 KER : Brittney Bailey \, PhD\, Assistant Professor\, Department of Mathem
 atics of Statistics\, Amherst College TITLE : “Multiple Imputation by Pre
 dictive Mean Matching in Cluster-Randomized Trials" ABSTRACT : Multiple i
 mputation using random effects regression imputation has been recommended
  for cluster randomized trials (CRTs) because it is congenial to the appr
 opriate analytic model for CRTs. This imputation method relies on paramet
 ric assumptions and may not be robust to misspecification of the imputati
 on model. Imputation by predictive mean matching (PMM) is a semiparametri
 c alternative\, but implementation of PMM for multilevel data is limited 
 in current software. For some time\, only imputation models that ignore c
 lustering or use fixed effects for clusters could be used for imputation\
 , resulting in underestimation (ignoring clustering) or overestimation (f
 ixed effects for clusters) of variance estimates. This talk will discuss 
 and compare approaches to handling multiple imputation by predictive mean
  matching with a focus on procedures that can be readily implemented with
  existing software.\n\nSpeaker:\nBrittney Bailey\, PhD\n\nAdmission:\nFre
 e\n\nDetails URL:\nhttps://medicine.yale.edu/event/ysph-biostatistics-vir
 tual-seminar-tba-copy-8/\n
DTEND;TZID=America/New_York:20211019T130000
DTSTAMP:20261018T140344Z
DTSTART;TZID=America/New_York:20211019T120000
GEO:41.302961;-72.931638
LOCATION:106-A\, 47 College Street\, New Haven\, CT\, United States
SEQUENCE:0
STATUS:Confirmed
SUMMARY:YSPH Biostatistics Seminar: "Multiple Imputation by Predictive Mea
 n Matching in Cluster-Randomized Trials"
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