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PRODID:Data::ICal 0.24
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TZID:Pacific/Auckland
X-LIC-LOCATION:Pacific/Auckland
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DTSTART:19700927T020000
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BEGIN:VEVENT
CATEGORIES:SMS Seminars
CONTACT:Dr. Nokuthaba Sibanda 
DESCRIPTION:The problem of non-unique cell classification in categorical da
 ta arises when the cell that an observation falls in cannot be uniquely id
 entified.  This problem is further compounded when data for some of the ca
 tegories is sparse.  We compare two approaches for Bayesian estimation of 
 multinomial cell probabilities in such circumstances. One approach is base
 d on an exact likelihood and the other is based on an augmented data likel
 ihood.  \nThe failure of correct chromosome separation (non-disjunction) l
 eads to genetic disorders\, such as trisomy 21 which causes Downs Syndrome
 . For a given nuclear family\, it may not be possible to uniquely identify
  the parental origin of non-disjunction.  The methods described above are 
 demonstrated in estimating probabilities of maternal and paternal meiotic 
 non-disjunction.  The results are checked against laboratory results obtai
 ned using information from numerous gene locations. 
DTEND;TZID=Pacific/Auckland:20091001T160000
DTSTAMP:20260423T181522Z
DTSTART;TZID=Pacific/Auckland:20091001T150000
LOCATION:Cotton Club\, Cotton 350
ORGANIZER:Dr. Nokuthaba Sibanda 
SUMMARY:Dr. Nokuthaba Sibanda  - Bayesian estimation of multinomial probabi
 lities with non-unique cell classification: Application to trisomy 21 data
  
UID:seminar_sms669_20090925103925
URL:
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